At least one beginner machine learning course.If you don’t know what that means, spend another month or two writing Python code and then come back here. Can you write a Python function which accepts and uses parameters? That’s good enough. What do I need to know to go through this course? If no, go and do a beginner machine learning course and if you decide you want to learn TensorFlow, this page will still be here. Have you done at least one beginner machine learning course and would like to learn about deep learning/pass the TensorFlow Developer Certification? If yes, no you shouldn't, use your skills to build something. Should you do this course?ĭo you have 1+ years experience with deep learning and writing TensorFlow code? If you've got 6-months experience writing Python code and a willingness to learn (most important), you'll be able to do the course. This means we write code first then step through the concepts behind it. The goal is to get you writing deep learning code as soon as possible.Ĭode -> Concept -> Code -> Concept -> Code -> Concept Preparing to Pass the TensorFlow Developer Certification Exam TensorFlow Time Series Fundamentals & Milestone Project 3: BitPredict □□ Pubmed_RCT_200k_dataset, skimlit_tribrid_model Milestone Project 1: Food Vision □□, Template (your challenge)įeature_extraction_mixed_precision_efficientnet_model, fine_tuned_mixed_precision_efficientnet_modelĭiaster_or_no_diaster_tweets, USE_feature_extractor_model Transfer Learning Part 1: Feature extractionġ0_food_classes_10_percent, 10_food_classes_1_percent, 10_food_classes_all_dataġ01_food_classes_10_percent, custom_food_images, fine_tuned_efficientnet_model Note: You can get all of the notebook code created during the videos in the video_notebooks directory. Slides: Although we focus on writing TensorFlow code, we sometimes use pretty slides to describe different concepts, you'll find them here.Exercises & Extra-curriculum: Each module comes with a set of exercises and extra-curriculum to help practice your skills and learn more, I suggest going through these before you move onto the next module.Data/model: Links to datasets/pre-trained models for the associated notebook.Notebook: The notebook for a particular module with lots of code and text annotations (notebooks from the videos are based on these).Number: The number of the target notebook (this may not match the video section of the course but it ties together all of the materials in the table).All the links you need for everything will be here. This table is the ground truth for course materials. - Added fix for TensorFlow 2.7.0+ for notebook 01, see discussion for more.- Added fix for TensorFlow 2.7.0+ for notebook 02, see discussion for more.tf.(learning_rate=0.001), old lr still works but is deprecated ![]() - Newer versions of TensorFlow (2.10+) use learning_rate instead of lr in tf.keras.optimizers (e.g.- Notebook 05 new namespaces added for tf.keras.layers, see #547, also add fix for issue with model.load_weights() in Notebook 05, see #544, if you're having trouble saving/loading the model weights, also see #553.- Update Notebook 06 for new TensorFlow namespaces (no major functionality change, just different imports), see: #549.- Update Notebook 07 for new version of TensorFlow + fix model loading errors (TensorFlow 2.13+ required), see: #550.- Update Notebook 08 for new version of TensorFlow + update Notebook 09 for new version of TensorFlow & spaCy, see update notes for 09: #557.In short, if you're using tf.0 and facing errors, swap to tf._v2.EfficientNetV2B0.- Update Notebook 05 to fix #544 and #553, see #575 for full notes.Ask a question (like to know more? go here).Exercises & Extra-curriculum (challenges to practice what you've learned and resources to learn more).Prerequisites (what skills you'll need to do this course).Should you do this course? (decide by answering a couple simple questions).Course structure (how this course is taught).Course materials (everything you'll need for completing the course).□ Get a quick overview of TensorFlow with the TensorFlow Cheatsheet.□ Got questions about the course? Check out the livestream Q&A for the course launch.□ Sign up to the full course on the Zero to Mastery Academy (videos for notebooks 03-10).□ Read the beautiful online book version of the course.□ Watch the first 14-hours of the course on YouTube (notebooks 00, 01, 02). ![]() This course will teach you the foundations of deep learning and TensorFlow as well as prepare you to pass the TensorFlow Developer Certification exam (optional). Zero to Mastery Deep Learning with TensorFlowĪll of the course materials for the Zero to Mastery Deep Learning with TensorFlow course.
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