TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
TranslatedDeep Learning Tutorial, excellent articles
FinRL®: Financial Reinforcement Learning. 🔥
:satellite: Simple and ready-to-use tutorials for TensorFlow
Your new Mentor for Data Science E-Learning.
Learn ML engineering for free in 4 months! Register here 👇🏼
Natural Language Processing Tutorial for Deep Learning Researchers
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
TranslatedOpen source Deep Learning book, based on TensorFlow 2.0 framework.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
TensorFlow Tutorials with YouTube Videos
Lab Materials for MIT 6.S191: Introduction to Deep Learning
TensorFlow examples
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
TranslatedTensorFlow 2 Chinese tutorials, continuously updated (current version: tensorflow2.0), tag: tensorflow 2.0 tutorials
The "Python Machine Learning (2nd edition)" book code repository and info resource
Python code for "Probabilistic Machine learning" book by Kevin Murphy
A course in reinforcement learning in the wild
TranslatedTensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0 version introductory example code and hands-on tutorials.