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This repository contains tutorials, assignments, and competitions for MIT's deep learning courses, covering a wide range of AI and machine learning topics.
A comprehensive Tensorflow 2.0 tutorial and learning resource for developers.
Simple reinforcement learning tutorials in Python using TensorFlow for AI/ML developers.
Comprehensive set of TensorFlow tutorials with accompanying YouTube videos for learning deep learning and machine learning.
Lab materials for an introductory course on deep learning from MIT, covering computer vision, music generation, and more.
A comprehensive collection of machine learning and deep learning resources for developers.
A deep learning and reinforcement learning library for scientists and engineers, with support for TensorFlow.
This GitHub repository provides a comprehensive collection of TensorFlow 2.x tutorials and examples for AI/ML developers.
TensorFlow documentation repository with code examples and tutorials for deep learning and machine learning.
A comprehensive deep learning course with TensorFlow focused on foundational concepts and practical applications.
A comprehensive TensorFlow tutorial covering a wide range of machine learning topics for AI-focused developers.
A comprehensive collection of tutorials and resources for AI, deep learning, and machine learning in Python.
A collection of implementations from a free course on deep reinforcement learning using TensorFlow and PyTorch.
This is a best practice for a TensorFlow project template architecture for developers building AI-powered applications.
This open-source Python library is a training platform for building deep learning models to recognize captchas.
Example TensorFlow codes and a TensorFlow as a Service dev environment for AI/ML developers.
A comprehensive collection of TensorFlow tutorials covering convolutional and recurrent neural networks.
YoloV3 object detection implemented in TensorFlow 2.0
Bare-bones examples of machine learning in TensorFlow for developers working with AI tools.
This GitHub repository is a comprehensive tutorial for learning machine learning in just two months, featuring Jupyter Notebooks and covering essential ML concepts.
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