Tensorflow keras

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Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial

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18.06.2020

This course will teach you how to use Keras, a neural network API written in Python and integrated with TensorFlow. We will learn how to prepare and process data for artificial neural networks, build and train artificial neural networks from scratch, build and train convolutional neural networks (CNNs), implement fine-tuning and transfer learning, and more! ⭐️🦎 COURSE CONTENTS 🦎⭐️ ⌨️ (00:00:00) Welcome to this course ⌨️ (00:00:16) Keras Course Introduction ⌨️ (00:00:50) Course Prerequisites ⌨️ (00:01:33) DEEPLIZARD Deep Learning Path ⌨️ (00:01:45) Course Resources ⌨️ (00:02:30) About Keras ⌨️ (00:06:41) Keras with TensorFlow - Data Processing for Neural Network Training ⌨️ (00:18:39) Create an Artificial Neural Network with TensorFlow's Keras API ⌨️ (00:24:36) Train an Artificial Neural Network with TensorFlow's Keras API ⌨️ (00:30:07) Build a Validation Set With TensorFlow's Keras API ⌨️ (00:39:28) Neural Network Predictions with TensorFlow's Keras API ⌨️ (00:47:48) Create a Confusion Matrix for Neural Network Predictions ⌨️ (00:52:29) Save and Load a Model with TensorFlow's Keras API ⌨️ (01:01:25) Image Preparation for CNNs with TensorFlow's Keras API ⌨️ (01:19:22) Build and Train a CNN with TensorFlow's Keras API ⌨️ (01:28:42) CNN Predictions with TensorFlow's Keras API ⌨️ (01:37:05) Build a Fine-Tuned Neural Network with TensorFlow's Keras API ⌨️ (01:48:19) Train a Fine-Tuned Neural Network with TensorFlow's Keras API ⌨️ (01:52:39) Predict with a Fine-Tuned Neural Network with TensorFlow's Keras API ⌨️ (01:57:50) MobileNet Image Classification with TensorFlow's Keras API ⌨️ (02:11:18) Process Images for Fine-Tuned MobileNet with TensorFlow's Keras API ⌨️ (02:24:24) Fine-Tuning MobileNet on Custom Data Set with TensorFlow's Keras API ⌨️ (02:38:59) Data Augmentation with TensorFlow' Keras API ⌨️ (02:47:24) Collective Intelligence and the DEEPLIZARD HIVEMIND ⭐️🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎⭐️ 👉 Check out the blog post and other resources for this course: 🔗 🤍 💻 DOWNLOAD ACCESS TO CODE FILES 🤖 Available for members of the deeplizard hivemind: 🔗 🤍 🧠 Support collective intelligence, join the deeplizard hivemind: 🔗 🤍 👋 Hey, we're Chris and Mandy, the creators of deeplizard! 👀 CHECK OUT OUR VLOG: 🔗 🤍 👀 Follow deeplizard: YouTube: 🤍 Our vlog: 🤍 Facebook: 🤍 Instagram: 🤍 Twitter: 🤍 Patreon: 🤍 🎵 deeplizard uses music by Kevin MacLeod 🔗 🤍 🔗 🤍 ❤️ Please use the knowledge gained from deeplizard content for good, not evil. Learn to code for free and get a developer job: 🤍 Read hundreds of articles on programming: 🤍 And subscribe for new videos on technology every day: 🤍

Deep Learning with Python, TensorFlow, and Keras tutorial

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An updated deep learning introduction using Python, TensorFlow, and Keras. Text-tutorial and notes: 🤍 TensorFlow Docs: 🤍 Keras Docs: 🤍 Discord: 🤍

TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka

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06.05.2019

AI and Deep-Learning with TensorFlow - 🤍 This Edureka video provides you with a basic introduction to TensorFlow: The amazing deep learning framework by Google. Below are the topics covered in this video: 1. What is TensorFlow? 2. Companies using TensorFlow 3. Features of TensorFlow 4. What are Tensors? 5. What are Neural Networks? 6. TensorFlow Open Source Community Complete Tensorflow Playlist: 🤍 PG in Artificial Intelligence and Machine Learning with NIT Warangal : 🤍 Post Graduate Certification in Data Science with IIT Guwahati - 🤍 (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) Join our Meetup group and never miss any free live webinar: 🤍 Subscribe to our Edureka YouTube channel to get video updates: 🤍 Instagram: 🤍 Slideshare: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 For more information, Please write back to us at sales🤍edureka.in or call us at: IND: 9606058406 / US: 18338555775 (toll free) About the course: Edureka's Deep Learning in TensorFlow with Python Certification Training is curated by industry professionals as per the industry requirements & demands. You will master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. The course has been specially curated by industry experts with real-time case studies. Objectives: Deep Learning in TensorFlow with Python Training is designed by industry experts to make you a Certified Deep Learning Engineer. The Deep Learning in TensorFlow course offers: In-depth knowledge of Deep Neural Networks Comprehensive knowledge of various Neural Network architectures such as Convolutional Neural Network, Recurrent Neural Network, Autoencoders Implementation of Collaborative Filtering with RBM The exposure to real-life industry-based projects which will be executed using TensorFlow library Rigorous involvement of an SME throughout the AI & Deep Learning Training to learn industry standards and best practices - Why should one go for this course? Deep Learning is one of the most accelerating and promising fields, among all the technologies available in the IT market today. To become an expert in this technology, you need structured training with the latest skills as per current industry requirements and best practices. Besides strong theoretical understanding, you will be working on various real-life data projects using different neural network architectures as a part of the solution strategy. Additionally, you will receive guidance from a Deep Learning expert who is currently working in the industry on real-life projects. - Skills that you will be learning: Deep Learning in TensorFlow with Python Training will help you to become a Deep Learning Engineer. It will hone your skills by offering you comprehensive knowledge on Deep Learning in TensorFlow. It will also acquaint you with the required hands-on experience for solving real-time industry-based Deep Learning projects. During this course you will be trained by our expert instructors on: Deep Learning and TensorFlow Concepts Working with Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) Proficiency in Long short-term memory (LSTM) Implementing Keras, TFlearn, Autoencoders Implementing Restricted Boltzmann Machine (RBM) Knowledge of Neural Networks & Natural Language Processing (NLP) Using Python with TensorFlow Libraries Perform Text Analytics Perform Text Processing Who should go for this course? The TensorFlow with Python Training is for all the professionals who are passionate about Deep Learning and want to go ahead and make their career as a Deep Learning Engineer. It is best suited for individuals who are: Developers aspiring to be a 'Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Deep Learning (ML) Techniques Information Architects who want to gain expertise in Predictive Analytics Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused on one industry or skill set, it can be used by anyone to enhance their portfolio.

Keras vs Tensorflow | Deep Learning Frameworks Comparison | Intellipaat

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10.11.2019

🔥Intellipaat Artificial Intelligence Master's Course: 🤍 In this video on keras vs tensorflow you will understand about the top deep learning frameworks used in the IT industry, and which one should you use for better performance. So in this keras vs tensorflow comparison some important parameters have been taken into consideration to tell you the difference between keras and tensorflow also which one is preferred over the other in certain aspects in detail. #KerasvsTensorflow #DeepLearningFrameworksComparison #TensorflowvsKeras #Intellipaat 📌 Do subscribe to Intellipaat channel & get regular updates on videos: 🤍 📕 Read complete Artificial Intelligence tutorial here: 🤍 📝Following topics are covered in this Keras vs Tensorflow comparison tutorial: 01:35 - What is Keras? 02:03 - What is Tensorflow? 02:40 - Differentiating between Keras and Tensorflow 05:21 - Benifits of using Keras 06:05 - Benifits of using Tensorflow 06:45 - Limitation of using Keras 07:45 - Limitation of using Tensorflow 09:00 - Popularity and trends in Keras and Tensorflow 10:00 - Which is better to choose? 11:40 -Quiz 🔗 Watch Artificial Intelligence video tutorials here: 🤍 📰Interested to learn Artificial Intelligence still more? Please check similar what is Artificial Intelligence Blog here: 🤍 If you’ve enjoyed this Keras vs Tensorflow which is better video, Like us and Subscribe to our channel for more similar informative videos and free tutorials. What do you think which one of them is better among Tensorflow vs Keras according to you? Tell us in the comment section below. Intellipaat Edge 1. 24*7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs 5. Industry Oriented Course ware 6. Life time free Course Upgrade Why Keras is important Keras is an Open Source Neural Network library written in Python that runs on top of Theano or Tensorflow. It is designed to be modular, fast and easy to use. Keras is very quick to make a network model. If you want to make a simple network model with a few lines, Keras can help you with that. Why Tensorflow is important TensorFlow is an open source machine learning framework for carrying out high-performance numerical computations. It provides excellent architecture support which allows easy deployment of computations across a variety of platforms ranging from desktops to clusters of servers, mobiles, and edge devices. For more Information: Please write us to sales🤍intellipaat.com, or call us at: +91- 7847955955 Website: 🤍 Facebook: 🤍 LinkedIn: 🤍 Telegram: 🤍 Instagram: 🤍 Twitter: 🤍

Keras vs TensorFlow vs Pytorch | Deep Learning Frameworks Comparison 2021 | Simplilearn

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30.01.2021

With the Deep Learning scene being dominated by three main frameworks, it is very easy to get confused on which one to use? In this video on Keras vs Tensorflow vs Pytorch, we will clear all your doubts on which framework is better and which framework should be used by beginners, intermediates, and professionals. 🔥Free Deep Learning Course: 🤍 The topics covered in this video are : 00:00:00 What is Keras, Tensorflow and Pytorch? 00:05:27 Differences between Keras, TensorFlow and Pytorch 00:11:46 Which framework should you use? Start learning today's most in-demand skills for FREE. Visit us at 🤍 Choose over 300 in-demand skills and get access to 1000+ hours of video content for FREE in various technologies like Data Science, Cybersecurity, Project Management & Leadership, Digital Marketing, and much more. ✅Subscribe to our Channel to learn more about the top Technologies: 🤍 ⏩ Check out the Deep Learning tutorial videos: 🤍 #KerasvsTensorflowvsPytorch #KerasvsTensorFlow #DeepLearningFrameworks #DeepLearningFrameworksComparision #ArtificialIntelligenceCourse #ArtificialIntelligenceTutorial #ArtificialIntelligenceTutorialForBeginners #Simplilearn Post Graduate Program in AI and Machine Learning: Ranked #1 AI and Machine Learning course by TechGig Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and Machine Learning covers statistics, Python, machine learning, deep learning networks, NLP, and reinforcement learning. You will build and deploy deep learning models on the cloud using AWS SageMaker, work on voice assistance devices, build Alexa skills, and gain access to GPU-enabled labs. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU enabled Labs ✅ 450+ hours of Applied learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program Certification ✅ Masterclasses from Purdue ✅Get noticed by the top hiring companies 👉Learn more at: 🤍 For more updates on courses and tips follow us on: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial

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Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence. Throughout the 8 modules in this course you will learn about fundamental concepts and methods in ML & AI like core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning. Each of these modules include in-depth explanations and a variety of different coding examples. After completing this course you will have a thorough knowledge of the core techniques in machine learning and AI and have the skills necessary to apply these techniques to your own data-sets and unique problems. ⭐️ Google Colaboratory Notebooks ⭐️ 📕 Module 2: Introduction to TensorFlow - 🤍 📗 Module 3: Core Learning Algorithms - 🤍 📘 Module 4: Neural Networks with TensorFlow - 🤍 📙 Module 5: Deep Computer Vision - 🤍 📔 Module 6: Natural Language Processing with RNNs - 🤍 📒 Module 7: Reinforcement Learning - 🤍 ⭐️ Course Contents ⭐️ ⌨️ (00:03:25) Module 1: Machine Learning Fundamentals ⌨️ (00:30:08) Module 2: Introduction to TensorFlow ⌨️ (01:00:00) Module 3: Core Learning Algorithms ⌨️ (02:45:39) Module 4: Neural Networks with TensorFlow ⌨️ (03:43:10) Module 5: Deep Computer Vision - Convolutional Neural Networks ⌨️ (04:40:44) Module 6: Natural Language Processing with RNNs ⌨️ (06:08:00) Module 7: Reinforcement Learning with Q-Learning ⌨️ (06:48:24) Module 8: Conclusion and Next Steps ⭐️ About the Author ⭐️ The author of this course is Tim Ruscica, otherwise known as “Tech With Tim” from his educational programming YouTube channel. Tim has a passion for teaching and loves to teach about the world of machine learning and artificial intelligence. Learn more about Tim from the links below: 🔗 YouTube: 🤍 🔗 LinkedIn: 🤍 Learn to code for free and get a developer job: 🤍 Read hundreds of articles on programming: 🤍 And subscribe for new videos on technology every day: 🤍

Getting Started with Keras

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14.08.2018

Getting started with Keras has never been easier! Not only is it built into TensorFlow, but when you combine it with Kaggle Kernels you don’t have to install anything! Plus you get to take advantage of the resources from the Kaggle community. In this episode of AI Adventures, Yufeng shows you how to get started with Keras. Take a look! Associated blog post → 🤍 Get started with Keras → 🤍 Previous video with Fashion-MNIST → 🤍 Watch more AI Adventures → 🤍 Subscribe to the Google Cloud Platform channel → 🤍 #AIAdventures

Inside TensorFlow: tf.Keras (Part 1)

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22.08.2019

Take an inside look into the TensorFlow team’s own internal training sessionstechnical deep dives into TensorFlow by the very people who are building it! On this episode of Inside TensorFlow, creator of Keras, Francois Chollet gives us the overview of tf.Keras. Let us know what you think about this presentation in the comments below and stay tuned for part 2 coming next week! TensorFlow on GitHub → 🤍 Watch more from Inside TensorFlow Playlist → 🤍 Subscribe to the TensorFlow channel → 🤍

Keras vs Tensorflow vs PyTorch | Deep Learning Frameworks Comparison | Edureka

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26.11.2018

AI & Deep Learning with Tensorflow Training: 🤍 This Edureka video on "Keras vs TensorFlow vs PyTorch" will provide you with a crisp comparison among the top three deep learning frameworks. It provides a detailed and comprehensive knowledge about Keras, TensorFlow and PyTorch and which one to use for what purposes. Following topics will be covered in this video: 1:06 - Introduction to keras, Tensorflow, Pytorch 2:13 - Parameters of Comparison 2:18 - Level of API 3:06 - Speed 3:28 - Architecture 4:03 - Ease of Code 4:27 - Debugging 4:59 - Community Support 5:19 - Datasets 5:37 - Popularity 6:14 - Suitable use cases Subscribe to our channel to get video updates. Hit the subscribe button above 🤍 PG in Artificial Intelligence and Machine Learning with NIT Warangal : 🤍 Post Graduate Certification in Data Science with IIT Guwahati - 🤍 (450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies) Instagram: 🤍 Facebook: 🤍 Twitter: 🤍 LinkedIn: 🤍 Check our complete Deep Learning With TensorFlow playlist here: 🤍 #keras #tensorflow #pytorch #deeplearning #machinelearning #frameworks - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders. Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course. - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. Business Analysts who want to understand Deep Learning (ML) Techniques 4. Information Architects who want to gain expertise in Predictive Analytics 5. Professionals who want to captivate and analyze Big Data 6. Analysts wanting to understand Data Science methodologies However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio. - - - - - - - - - - - - - - Why Learn Deep Learning With TensorFlow? TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning. - Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, please write back to us at sales🤍edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free). -

What is Keras and Tensorflow | Keras vs Tensorflow

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In this video, we will understand what is Keras and Tensorflow. Tensorflow is a free and open-source library for machine learning and artificial intelligence. It was developed by Google. And it can be used for developing large-scale machine learning applications, and it is also highly used by researchers to push the state of the art in machine learning. Keras is also an open-source library for machine learning and neural network but it higher-level API compared to Tensorflow and can run on top of Tensorflow. Training of model and execution is fast in Tensorflow, while it is slow in Keras. Thus Keras is used mainly for rapid prototyping and applications dealing with small datasets. Whereas, Tensorflow is used for creating large-scale applications. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Timestamps: 0:00 Keras and Tensorflow Overview 1:45 Difference between Keras and Tensorflow 3:02 End ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Follow my entire playlist on Convolutional Neural Network (CNN) : 📕 CNN Playlist: 🤍 At the end of some videos, you will also find quizzes 📑 that can help you to understand the concept and retain your learning. ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ✔ Complete Neural Network Playlist:🤍 ✔ Complete Logistic Regression Playlist: 🤍 ✔ Complete Linear Regression Playlist: 🤍 ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ If you want to ride on the Lane of Machine Learning, then Subscribe ▶ to my channel here: 🤍

Pytorch vs Tensorflow vs Keras | Deep Learning Tutorial 6 (Tensorflow Tutorial, Keras & Python)

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We will go over what is the difference between pytorch, tensorflow and keras in this video. Pytorch and Tensorflow are two most popular deep learning frameworks. Pytorch is by facebook and Tensorflow is by Google. Keras is not a full fledge deep learning framework, it is just a wrapper around Tensorflow that provides some convenient APIs. 🔖 Hashtags 🔖 #pytorch #tensorflow #keras #tensorflowtutorial #keratutorial #pytorchtutorial Next video: 🤍 Previous video: 🤍 Deep learning playlist: 🤍 Prerequisites for this series:    1: Python tutorials (first 16 videos): 🤍     2: Pandas tutorials(first 8 videos): 🤍 3: Machine learning playlist (first 16 videos): 🤍   Website: 🤍 Facebook: 🤍 Twitter: 🤍

What is Keras | What is TensorFlow | Keras and TensorFlow Tutorial For Beginners - Intellipaat

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🔥Intellipaat Artificial Intelligence course: 🤍 This tensorflow tutorial for beginners is a short video about what is tensorflow, why it is used, it’s features and the various objects it has. You will also learn about Keras and how Keras programming is used with tensorflow to build deep learning applications. Upon finishing watching this tensorflow keras tutorial video you will be well-versed in this deep learning library. 📌 Do subscribe to Intellipaat channel & get regular updates on videos: 🤍 🔗 Watch AI video tutorials here: 🤍 📕 Read complete AI tutorial here: 🤍 📰 Interested to learn Deep Learning still more? Please check similar blog here: 🤍 Below topics are explained in this Intellipaat deep learning with tensorflow beginner tutorial: 00:32 - introduction to tensorflow 01:55 - tensorflow objects 4:56 - what is keras 6:21 - career opportunities in ai In our Artificial Intelligence course, you will learn tensorflow, tensorflow basics with tensorflow example, case and projects and this will help you become a successful AI professional in future. You can get more details about our deep learning tensorflow course at: 🤍 It is a 32 hrs instructor led Artificial Intelligence training provided by Intellipaat which is completely aligned with industry standards and certification bodies. Interested to learn more about google tensorflow? Please check similar blogs here: 🤍 Watch artificial intelligence and machine learning tutorials here: 🤍 If you’ve enjoyed this keras vs tensorflow video, like the video and subscribe to our channel for more similar informative videos. Got any questions about tensorflow explained? Ask us in the comment section below. Intellipaat Edge 1. 24*7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs 5. Industry Oriented Course ware 6. Life time free Course Upgrade Why Artificial Intelligence is important? Artificial Intelligence is taking over each and every industry domain. Machine Learning and especially Deep Learning are the most important aspects of Artificial Intelligence that are being deployed everywhere from search engines to online movie recommendations. Taking the Intellipaat Deep Learning training & Artificial Intelligence Course can help professionals to build a solid career in a rising technology domain and get the best jobs in top organizations. Why should you opt for an Artificial Intelligence career? If you want to fast-track your career then you should strongly consider Artificial Intelligence. The reason for this is that it is one of the fastest growing technology. There is a huge demand for professionals in Artificial Intelligence. The salaries for A.I. Professionals is fantastic.There is a huge growth opportunity in this domain as well. Hence this Intellipaat video is your stepping stone to a successful career! #Keras #WhatIsTensorFlow #TensorFlowTutorialForBeginners For more Information: Please write us to sales🤍intellipaat.com, or call us at: +91- 7847955955, US : 1-800-216-8930(Toll Free) Website: 🤍 Facebook: 🤍 LinkedIn: 🤍 Twitter: 🤍

TensorFlow And Keras Tutorial | Deep Learning With TensorFlow & Keras | Deep Learning | Simplilearn

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05.03.2021

This video on TensorFlow and Keras tutorial will help you understand Deep Learning frameworks, what is TensorFlow, TensorFlow features and applications, how TensorFlow works, TensorFlow 1.0 vs TensorFlow 2.0, TensorFlow architecture with a demo. Then we will move into understanding what is Keras, models offered in Keras, what are neural networks and they work. 🔥Free TensorFlow Course: 🤍 00:00:00 Deep Learning frameworks 00:03:01 What is TensorFlow 00:03:21 TensorFlow features and applications 00:07:46 How TensorFlow works 00:09:11 TensorFlow 1.0 vs TensorFlow 2.0 00:16:51 TensorFlow architecture with a demo. ✅Subscribe to our Channel to learn more about the top Technologies: 🤍 ⏩ Check out the Machine Learning tutorial videos: 🤍 #TensorFlowAndKerasTutorial #TensorFlowTutorial #KerasTutorial #TensorFlowAndKerasTutorialForBeginners #DeepLearningWithTensorFlowAndKeras #DeepLearningTutorial #DeepLearningTutorialForBeginners #DeepLearning #Simplilearn Post Graduate Program in AI and Machine Learning: Ranked #1 AI and Machine Learning course by TechGig Fast track your career with our comprehensive Post Graduate Program in AI and Machine Learning, in partnership with Purdue University and in collaboration with IBM. This AI and machine learning certification program will prepare you for one of the world’s most exciting technology frontiers. This Post Graduate Program in AI and Machine Learning covers statistics, Python, machine learning, deep learning networks, NLP, and reinforcement learning. You will build and deploy deep learning models on the cloud using AWS SageMaker, work on voice assistance devices, build Alexa skills, and gain access to GPU-enabled labs. Key Features: ✅ Purdue Alumni Association Membership ✅ Industry-recognized IBM certificates for IBM courses ✅ Enrollment in Simplilearn’s JobAssist ✅ 25+ hands-on Projects on GPU enabled Labs ✅ 450+ hours of Applied learning ✅ Capstone Project in 3 Domains ✅ Purdue Post Graduate Program Certification ✅ Masterclasses from Purdue ✅Get noticed by the top hiring companies 👉Learn more at: 🤍 For more information about Simplilearn’s courses, visit: - Facebook: 🤍 - Twitter: 🤍 - LinkedIn: 🤍 - Website: 🤍 - Instagram: 🤍 - Telegram Mobile: 🤍 - Telegram Desktop: 🤍 Get the Android app: 🤍 Get the iOS app: 🤍

Aprende a PROGRAMAR una RED NEURONAL - Tensorflow, Keras, Sklearn

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📚 [El registro al bootcamp ya ha finalizado] - LINKS DEL VÍDEO - 💻 Código Tensorflow, Keras y Sklearn : 🤍 - ¡MÁS DOTCSV! 💸 Patreon : 🤍 👓 Facebook : 🤍 👾 Twitch!!! : 🤍 🐥 Twitter : 🤍 📸 Instagram : 🤍 - ¡MI TECNOLOGÍA! Aquí no está toda mi tecnología, sólo aquella que realmente recomiendo. Usando estos links de Amazon yo me llevaré una comisión por tu compra :) [Tecnología básica para Youtube] 💻 Portátil - MSI GP72 7RDX Leopard : 🤍 📸 Cámara - Canon EOS 750D : 🤍 👁‍🗨 Objetivo 1 - EF 50 mm, F/1.8 : 🤍 👁‍🗨 Objetivo 2 - EF-S 18-135mm : 🤍 👁‍🗨 Objetivo 3 - EF 24 mm, F/2.8 : 🤍 🎤 Microfono - Blue Yeti Micro : 🤍 💡 Foco Luz - Foco LED Neewer : 🤍 🌈 Luz Color - Tira ALED Light : 🤍 [Mis otros cacharros] 📱 Smartphone - Google Pixel 2 XL : 🤍 ¡MÁS CIENCIA! - 🔬 Este canal forma parte de la red de divulgación de SCENIO. Si quieres conocer otros fantásticos proyectos de divulgación entra aquí: 🤍 #Scenio

Convolutional Neural Networks - Deep Learning basics with Python, TensorFlow and Keras p.3

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19.08.2018

Welcome to a tutorial where we'll be discussing Convolutional Neural Networks (Convnets and CNNs), using one to classify dogs and cats with the dataset we built in the previous tutorial. Text tutorials and sample code: 🤍 Discord: 🤍 Support the content: 🤍 Twitter: 🤍 Facebook: 🤍 Twitch: 🤍 G+: 🤍

TensorFlow Tutorial 8 - Model Subclassing with Keras

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00:22:59
15.08.2020

In this video we learn how to build much more flexible models using keras subclassing. Previously we've seen how to use Sequential and Functional API and hopefully the example demonstrated in the video shows the power of subclassing. I show how to build a ResNet-like model with skip connections which wouldn't even be possible using the Sequential API. Watch this video to understand ResNet: 🤍 I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link. affiliate: 🤍 non-affiliate: 🤍 GitHub Repository: 🤍 ✅ Equipment I use and recommend: 🤍 ❤️ Become a Channel Member: 🤍 ✅ One-Time Donations: Paypal: 🤍 Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc ▶️ You Can Connect with me on: Twitter - 🤍 LinkedIn - 🤍 GitHub - 🤍 TensorFlow Playlist: 🤍

Keras - установка и первое знакомство | #7 нейросети на Python

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30.06.2020

Установка пакета Keras - оболочки над TensorFlow. Сервис colabs от Google для экспериментов по построению и обучению нейросетей. Пример использования API Keras для задачи перевода градусов Цельсия в градусы Фаренгейта. Последовательная модель нейронной сети (keras.Sequential). Создание полносвязного слоя нейронов (Dense). Линейная активационная функция: activation='linear'. Компиляция модели сети: model.compile(). Запуск обучения сети: model.fit(). Подача на вход сети данных и вычисление выходного значения: model.predict(). Получение значений весовых коэффициентов: model.get_weights(). Инфо-сайт: 🤍 lesson 7. keras_grads.py: 🤍 Коллаборатория Google: 🤍 Keras (документация): 🤍

TENSORFLOW & KERAS ile DERİN ÖĞRENMEYE GİRİŞ | PYTHON ile YAPAY SİNİR AĞLARI

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13.09.2020

Python tensorflow keras ile derin öğrenme makine öğrenmesi scikit learn yapay zeka dersleri veri bilimi analizi yapay sinir ağları tutorial tirendaz akademi kanalında bulabilirsiniz. Bize destek olmak ve avantajlardan yararlanmak için kanalımıza katılın : 🤍 Merhaba, Tirendaz Akademiye hoşgeldiniz, Bu derste keras ve tensorflow anlattım. Özetle bu derste; 1-Keras nasıl yüklenir? 2-Derin öğrenme 3-Keras ile pratik veri analizi 4-Model sonuçları nasıl yorumlanır? gibi konuları anlattım. İyi seyirler... Veri seti için link: 🤍 Kanalımızda 400 den fazla eğitim dersi var. Bu derslerin oynatma listelerine aşağıdaki linklerden ulaşabilirsiniz. Derin öğrenme dersleri : 🤍 Makine öğrenmesi dersleri : 🤍 Python dersleri : 🤍 Pandas dersleri : 🤍 Django dersleri : 🤍 Python kütüphaneleri :🤍 Flask dersleri : 🤍 Veri görselleştirme : 🤍 1 videoda öğren dersleri : 🤍 Adettendir videomuzu beğenmeyi ve kanalımıza abone olmayı unutmayın !!! Öğrenmeyi seven ve sevdirerek öğreten akademi... Tirendaz Akademi #deeplearning #keras #tensorflow

เริ่มทำ Deep Learning ง่ายโคตรด้วย Keras, Tensorflow, Python | Object Classification

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31.05.2020

ในปัจจุบันเทคโนโลยีได้เปลี่ยนไปอย่างมาก หนึ่งในเทคโนโลยีที่น่าสนใจคือ ปัญญาประดิษฐ์ หรือ AI ในการที่เราจะสามารถสร้างเทคโนโลยีนี้ขึ้นมาจำเป็นที่ต้องใช้ความรู้เฉพาะทางหลายอย่าง หนึ่งในความรู้นั้นคือการโปรแกรมมิ่ง คลิปวิดีโอนี้จะมาสอนการใช้ Library ชื่อดังอย่าง Keras ที่มีการใช้ Tensorflow ในการทำงานเบื้องหลังเพื่อใช้ในการจำแนกสิ่งของหรือ Object Classification ในคลิปจะแบ่งเป็นสองส่วนคือส่วนที่จะพูดถึงความเป็นมาของ Neural Network กับส่วนcoding โดยส่วนcodingจะใช้ตัว Jupyter Notebookในการอธิบาย code อย่างละเอียดทีละบรรทัด Code: 🤍 Supported by: AI & ROBOTICS VENTURES (ARV) 🤍

Build and Train a Convolutional Neural Network with TensorFlow's Keras API

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28.07.2020

In this episode, we'll demonstrate how to build a simple convolutional neural network (CNN) and train it on images of cats and dogs using TensorFlow's Keras API. 🕒🦎 VIDEO SECTIONS 🦎🕒 00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources 00:35 Build a Simple CNN 06:19 Train a Simple CNN 09:25 Collective Intelligence and the DEEPLIZARD HIVEMIND 💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥 👋 Hey, we're Chris and Mandy, the creators of deeplizard! 👀 CHECK OUT OUR VLOG: 🔗 🤍 👉 Check out the blog post and other resources for this video: 🔗 🤍 💻 DOWNLOAD ACCESS TO CODE FILES 🤖 Available for members of the deeplizard hivemind: 🔗 🤍 🧠 Support collective intelligence, join the deeplizard hivemind: 🔗 🤍 🤜 Support collective intelligence, create a quiz question for this video: 🔗 🤍 🚀 Boost collective intelligence by sharing this video on social media! ❤️🦎 Special thanks to the following polymaths of the deeplizard hivemind: Tammy Prash Zach Wimpee 👀 Follow deeplizard: Our vlog: 🤍 Facebook: 🤍 Instagram: 🤍 Twitter: 🤍 Patreon: 🤍 YouTube: 🤍 🎓 Deep Learning with deeplizard: Fundamental Concepts - 🤍 Beginner Code - 🤍 Intermediate Code - 🤍 Advanced Deep RL - 🤍 🎓 Other Courses: Data Science - 🤍 Trading - 🤍 🛒 Check out products deeplizard recommends on Amazon: 🔗 🤍 📕 Get a FREE 30-day Audible trial and 2 FREE audio books using deeplizard's link: 🔗 🤍 🎵 deeplizard uses music by Kevin MacLeod 🔗 🤍 🔗 🤍 ❤️ Please use the knowledge gained from deeplizard content for good, not evil.

How to Build a Neural Network with TensorFlow and Keras in 10 Minutes

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05.11.2019

This is a short tutorial on How to build a Neural Network in Python with TensorFlow and Keras in just about 10 minutes Full TensorFlow Tutorial below Tutorial 1 - Setup of Tensorflow and keras 🤍 Tutorial 2 - Import and view the MNIST Fashion Dataset 🤍 Tutorial 3 - Examine the Image Data 🤍 Tutorial 4 - Preprocessing 🤍 Tutorial 5 - Setup Neural Network Layers 🤍 Tutorial 6 - Compile the Model 🤍 Tutorial 7 - Train the Model 🤍 Tutorial 8 - Make Predictions 🤍 Tutorial 9 - Evaluate Model Results(1) 🤍 Tutorial 10 - Evaluate Model Results(2) 🤍 Tutorial 11 - Prediction on Single Image 🤍 How to Setup TensorFlow and Keras with Anaconda Navigator 🤍 How to build a simple Neural Network - 🤍 To Learn Python: 🤍kindsonthegenius.com/python Machine Learning 101: 🤍 Subscribe Kindson The Genius Youtube: 🤍 Join Machine Learning & Data Science in Python and R - 🤍 Join my group ICS on Facebook: 🤍 Follow me on Instagram - 🤍 Connect with me on LinkedIn: 🤍 Follow me on Twitter: 🤍 Learn about me: 🤍 Tutorial 6. Creating Interactive 3D Plots - 🤍 How to Perform Linear Regression in R - 🤍 How to Perform Linear Regression in Python - 🤍 How to build a Neural Network in Python with TensorFlow and Keras for Data Science and Machine Learning

TensorFlow and Keras GPU Support - CUDA GPU Setup

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21.05.2020

In this episode, we'll discuss GPU support for TensorFlow and the integrated Keras API and how to get your code running with a GPU! 🕒🦎 VIDEO SECTIONS 🦎🕒 00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources 00:30 Help deeplizard add video timestamps - See example in the description 15:24 Collective Intelligence and the DEEPLIZARD HIVEMIND 💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥 👋 Hey, we're Chris and Mandy, the creators of deeplizard! 👀 CHECK OUT OUR VLOG: 🔗 🤍 👉 Check out the blog post and other resources for this video: 🔗 🤍 💻 DOWNLOAD ACCESS TO CODE FILES 🤖 Available for members of the deeplizard hivemind: 🔗 🤍 🧠 Support collective intelligence, join the deeplizard hivemind: 🔗 🤍 🤜 Support collective intelligence, create a quiz question for this video: 🔗 🤍 🚀 Boost collective intelligence by sharing this video on social media! ❤️🦎 Special thanks to the following polymaths of the deeplizard hivemind: Tammy Prash Zach Wimpee 👀 Follow deeplizard: Our vlog: 🤍 Facebook: 🤍 Instagram: 🤍 Twitter: 🤍 Patreon: 🤍 YouTube: 🤍 🎓 Deep Learning with deeplizard: Fundamental Concepts - 🤍 Beginner Code - 🤍 Intermediate Code - 🤍 Advanced Deep RL - 🤍 🎓 Other Courses: Data Science - 🤍 Trading - 🤍 🛒 Check out products deeplizard recommends on Amazon: 🔗 🤍 📕 Get a FREE 30-day Audible trial and 2 FREE audio books using deeplizard's link: 🔗 🤍 🎵 deeplizard uses music by Kevin MacLeod 🔗 🤍 🔗 🤍 ❤️ Please use the knowledge gained from deeplizard content for good, not evil.

Transfer Learning | Deep Learning Tutorial 27 (Tensorflow, Keras & Python)

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23.11.2020

📺 Transfer learning is a very important concept in the field of computer vision and natural language processing. Using transfer learning you can use pre trained model and customize it for your needs. This saves computation time and money. It has been a revolutionary break through in the field of deep learning and nowadays you see it being used widely in the industry. In this video we will go over some theory behind transfer learning and then use google's mobile net v2 pre trained model to train our flowers dataset Code: 🤍 Deep learning playlist: 🤍 Machine learning playlist : 🤍   #️⃣ Social Medias #️⃣ 🔗 Discord: 🤍 📸 Instagram: 🤍 🌎 Website: 🤍 🔊 Facebook: 🤍 📱 Twitter: 🤍 📝 Linkedin: 🤍 ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

Autoencoders in Python with Tensorflow/Keras

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01.03.2021

Text-based tutorial and sample code: 🤍 Neural Networks from Scratch book: 🤍 Channel membership: 🤍 Discord: 🤍 Reddit: 🤍 Support the content: 🤍 Twitter: 🤍 Instagram: 🤍 Facebook: 🤍 Twitch: 🤍

Image Preparation for Convolutional Neural Networks with TensorFlow's Keras API

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00:18:32
16.07.2020

In this episode, we'll go through all the necessary image preparation and processing steps to get set up to train our first convolutional neural network (CNN) using TensorFlow's Keras API. 🕒🦎 VIDEO SECTIONS 🦎🕒 00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for learning resources 00:26 Obtain the Data 00:41 Organize the Data 08:05 Process the Data 13:29 Visualize the Data 18:02 Collective Intelligence and the DEEPLIZARD HIVEMIND 💥🦎 DEEPLIZARD COMMUNITY RESOURCES 🦎💥 👋 Hey, we're Chris and Mandy, the creators of deeplizard! 👀 CHECK OUT OUR VLOG: 🔗 🤍 👉 Check out the blog post and other resources for this video: 🔗 🤍 💻 DOWNLOAD ACCESS TO CODE FILES 🤖 Available for members of the deeplizard hivemind: 🔗 🤍 🧠 Support collective intelligence, join the deeplizard hivemind: 🔗 🤍 🤜 Support collective intelligence, create a quiz question for this video: 🔗 🤍 🚀 Boost collective intelligence by sharing this video on social media! ❤️🦎 Special thanks to the following polymaths of the deeplizard hivemind: Tammy Prash Zach Wimpee 👀 Follow deeplizard: Our vlog: 🤍 Facebook: 🤍 Instagram: 🤍 Twitter: 🤍 Patreon: 🤍 YouTube: 🤍 🎓 Deep Learning with deeplizard: Fundamental Concepts - 🤍 Beginner Code - 🤍 Intermediate Code - 🤍 Advanced Deep RL - 🤍 🎓 Other Courses: Data Science - 🤍 Trading - 🤍 🛒 Check out products deeplizard recommends on Amazon: 🔗 🤍 📕 Get a FREE 30-day Audible trial and 2 FREE audio books using deeplizard's link: 🔗 🤍 🎵 deeplizard uses music by Kevin MacLeod 🔗 🤍 🔗 🤍 ❤️ Please use the knowledge gained from deeplizard content for good, not evil.

Tensorflow Input Pipeline | tf Dataset | Deep Learning Tutorial 44 (Tensorflow, Keras & Python)

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10.06.2021

Tensorflow tf.Data api allows you to build a data input pipeline. Using this you can handle large dataset for your deep learning training by streaming training samples from hard disk or S3 storage. tf.data.Dataset is the main class in tf.data api. In this video we see how tf pipeline allows not only to stream the data for training but you can peform various transformations easily by writing a single line of code. Code: 🤍 Exercise: 🤍 Stackoverflow article: 🤍 ⭐️ Timestamps ⭐️ 00:00 Introduction 00:21 Theory 07:58 Coding 31:34 Exercise Deep learning playlist: 🤍 Machine learning playlist : 🤍   🌎 Website: 🤍 🎥 Codebasics Hindi channel: 🤍 #️⃣ Social Media #️⃣ 🔗 Discord: 🤍 📸 Instagram: 🤍 🔊 Facebook: 🤍 📱 Twitter: 🤍 📝 Linkedin (Personal): 🤍 📝 Linkedin (Codebasics): 🤍 ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

【Keras】使用迁移学习再挑战 - CIFAR-10 by Transfer Learning - tensorflow, keras

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11.07.2020

【Keras】使用迁移学习再挑战 - CIFAR-10 by Transfer Learning - tensorflow, keras

[TensorFlow 2.x 강의 03] Keras (케라스)

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00:22:44
29.07.2020

1. 케라스 개요 2. 케라스 모델 3. 케라스 개발과정 3.1 데이터 생성 3.2 모델 구축 3.3 모델 컴파일 및 모델 학습 3.4 모델 평가 및 저장 4. 케라스 예제

TensorFlow Tutorial 14 - Callbacks with Keras and Writing Custom Callbacks

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25.08.2020

In this video we look at ways to customize model behavior during training and testing using Keras Callbacks. Specifically we look at ways how to save model during training epochs, using a learning rate scheduler and an example of a simple custom callbacks. I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link. affiliate: 🤍 non-affiliate: 🤍 GitHub Repository: 🤍 ✅ Equipment I use and recommend: 🤍 ❤️ Become a Channel Member: 🤍 ✅ One-Time Donations: Paypal: 🤍 Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc ▶️ You Can Connect with me on: Twitter - 🤍 LinkedIn - 🤍 GitHub - 🤍 TensorFlow Playlist: 🤍

Simple Explanation of LSTM | Deep Learning Tutorial 36 (Tensorflow, Keras & Python)

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06.02.2021

LSTM or long short term memory is a special type of RNN that solves traditional RNN's short term memory problem. In this video I will give a very simple explanation of LSTM using some real life examples so that you can understand this difficult topic easily. Also refer to following blogs to explore math and understand few more details. 🤍 Deep learning playlist: 🤍 Machine learning playlist : 🤍   🌎 Website: 🤍 🎥 Codebasics Hindi channel: 🤍 #️⃣ Social Media #️⃣ 🔗 Discord: 🤍 📸 Instagram: 🤍 🔊 Facebook: 🤍 📱 Twitter: 🤍 📝 Linkedin (Personal): 🤍 📝 Linkedin (Codebasics): 🤍 ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

Quickly get CSV into datasets for Keras (TensorFlow Tip of the Week)

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27.11.2018

Laurence Moroney (🤍lmoroney) gives you the quick breakdown on using Comma Separated Values (CSVs), with Keras. Watch to see how easy it is to train TensorFlow models from CSV data using Keras utilities. Stay tuned for more TensorFlow tips, and subscribe to the channel for the latest in machine learning! Learn more at → 🤍 See more TensorFlow tips→ 🤍 Subscribe to the TensorFlow channel! → 🤍

Text Classification Using BERT & Tensorflow | Deep Learning Tutorial 47 (Tensorflow, Keras & Python)

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28.08.2021

Using BERT and Tensorflow 2.0, we will write simple code to classify emails as spam or not spam. BERT will be used to generate sentence encoding for all emails and after that we will use a simple neural network with one drop out layer and one output layer. What is BERT? 🤍 Code: 🤍 Deep learning playlist: 🤍 Machine learning playlist: 🤍 🌎 Website: 🤍 🎥 Codebasics Hindi channel: 🤍 #️⃣ Social Media #️⃣ 🔗 Discord: 🤍 📸 Instagram: 🤍 🔊 Facebook: 🤍 📱 Twitter: 🤍 📝 Linkedin (Personal): 🤍 📝 Linkedin (Codebasics): 🤍 ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

Inside TensorFlow: tf.Keras (part 2)

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28.08.2019

Take an inside look into the TensorFlow team’s own internal training sessionstechnical deep dives into TensorFlow by the very people who are building it! This week we further take a look into tf.Keras as presented by the creator of Keras, Francois Chollet. Part 1 here: 🤍 Let us know what you think about this presentation in the comments below! TensorFlow on GitHub → 🤍 Watch more from Inside TensorFlow Playlist → 🤍 Subscribe to the TensorFlow channel → 🤍

TensorFlow 2.0 and Keras #AskTensorFlow

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03.07.2019

Developer Advocate Paige Bailey (🤍DynamicWebPaige) and TF Software Engineer Alex Passos answer your #AskTensorFlow questions. Remember to use #AskTensorFlow to have your questions answered in a future episode! 0:18 - What will be the support model for stand-alone Keras? 1:01 - Does tf.keras include everything that stand-alone Keras includes? 1:44 - What will TensorFlow 2.0 change to stand-alone Keras? 2:24 - Is there support for Bayesian layers in tf.keras? 2:54 - Can I create custom layers through tf.keras? 3:37 - Will the Keras namespace be removed in future releases of TF 2.0? 4:15 - Can we use SavedModel for a Keras model? Keras Special Interest Group: 🤍 Join the TF community: 🤍 TF Probability port for Bayesian Methods for Hackers: 🤍 This video is also subtitled in Chinese, Indonesian, Italian, Japanese, Korean, Portuguese, and Spanish. Subscribe to the TensorFlow channel → 🤍 Watch more episodes of #AskTensorFlow → 🤍

Balancing RNN sequence data - Deep Learning w/ Python, TensorFlow and Keras p.10

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17.09.2018

Welcome to the next part of our Deep Learning with Python, TensorFlow, and Keras tutorial series. In this tutorial, we're going to continue building our cryptocurrency-price-predicting Recurrent Neural Network. Text tutorials and sample code: 🤍 Discord: 🤍 Support the content: 🤍 Twitter: 🤍 Facebook: 🤍 Twitch: 🤍 G+: 🤍

Data augmentation to address overfitting | Deep Learning Tutorial 26 (Tensorflow, Keras & Python)

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01.11.2020

When we don't have enough training samples to cover diverse cases in image classification, often CNN might overfit. To address this we use a technique called data augmentation in deep learning. Data augmentation is used to generate new training samples from current training set using various transformations such as scaling, rotation, contrast change etc. In this video, we will classify flower images and see how our cnn model overfits. After that we will use data augmentation to generate new training samples and see how model performance improves. Code: 🤍 Deep learning playlist: 🤍 Machine learning playlist : 🤍   Discord: 🤍 Website: 🤍 Facebook: 🤍 Twitter: 🤍 Linkedin: 🤍 DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

What is YOLO algorithm? | Deep Learning Tutorial 31 (Tensorflow, Keras & Python)

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YOLO (You only look once) is a state of the art object detection algorithm that has become main method of detecting objects in the field of computer vision. Previously people used techniques such as sliding window object detection, R CNN, Fast R CNN and Faster R CNN. But after its invention in 2015, YOLO has become an industry standard for object detection due to its speed and accuracy. In this video we will understand the theory behind how exactly YOLO algorithm works. In next video we will write code to detect objects using YOLO framework. 🔖 Hashtags 🔖 #yoloalgorithm #yolodeeplearning #yoloobjectdetection #yolopython #yoloobjectdetection #yoloopencv Deep learning playlist: 🤍 Machine learning playlist : 🤍   🌎 Website: 🤍 #️⃣ Social Media #️⃣ 🔗 Discord: 🤍 📸 Instagram: 🤍 🔊 Facebook: 🤍 📱 Twitter: 🤍 📝 Linkedin: 🤍 ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

Stock Price Prediction Project with TensorFlow Keras ❌Make Money using Keras LSTM Neural Networks

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16.08.2020

In this hands-on Machine Learning with Python tutorial, we'll use LSTM Neural Networks from Tensorflow, more specifically the Keras library to predict stock prices. The purpose of this Deep Learning tutorial is to help you understand LSTMs better through a practical and relevant example and this example should not be used in a real world trading application as it serves just as a baseline machine /deep learning project that you can learn from. This content is intended to be used only for informational purposes and it's important to do your own analysis before making any investment. Therefore we strongly encourage you to dive deeper in this topic before starting your algorithmic trading with Machine Learning journey. 00:00 Deep Learning for stock price prediction 03:01 The goal 03:58 Start 06:45 Why and how to calculate price percentage change 09:54 Why use logarithmic returns for price prediction 12:45 Preprocessing 14:29 Train test split 15:26 Labeling and setting the time step required by the LSTM Neural Network 20:29 Reshaping the array / adding the temporal dimension 22:40 Create the LSTM Model for price prediction (part 1) 24:21 Deep Learning book recommendations 28:54 Create the LSTM Model for price prediction (part 2) 32:12 Calculate the root mean squared error (RMSE) You can access the Jupyter notebook here (login required): 🤍 🎁 1 MONTH FREE TRIAL! Financial and Alternative Datasets for today's Data Analysts & Scientists: 🤍 📚 RECOMMENDED DATA SCIENCE BOOKS: 🤍 ✅ Subscribe and support us: 🤍 💻 Data Science resources I strongly recommend: 🤍 🌐 Let's connect: 🤍 - At DecisionForest we serve both retail and institutional investors by providing them with the data necessary to make better decisions: 🤍 #DecisionForest

What is BERT? | Deep Learning Tutorial 46 (Tensorflow, Keras & Python)

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What is BERT (Bidirectional Encoder Representations From Transformers) and how it is used to solve NLP tasks? This video provides a very simple explanation of it. I am not going to go in details of how transformer based architecture works etc but instead I will go over an overview where you understand the usage of BERT in NLP tasks. In coding section we will generate sentence and word embeddings using BERT for some sample text. We will cover various topics such as, * Word2vec vc BERT * How BERT is trained on masked language model and next sentence completion task ⭐️ Timestamps ⭐️ 00:00 Introduction 00:39 Theory 11:00 Coding in tensorflow Code: 🤍 BERT article: 🤍 Word2Vec video: 🤍 Deep learning playlist: 🤍 Machine learning playlist : 🤍   🌎 Website: 🤍 🎥 Codebasics Hindi channel: 🤍 #️⃣ Social Media #️⃣ 🔗 Discord: 🤍 📸 Instagram: 🤍 🔊 Facebook: 🤍 📱 Twitter: 🤍 📝 Linkedin (Personal): 🤍 📝 Linkedin (Codebasics): 🤍 ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

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