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TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Learn how to design, develop, deploy and iterate on production-grade ML applications.
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.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
The fastai book, published as Jupyter Notebooks
This repository is primarily maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), ar…
📡 Simple and ready-to-use tutorials for TensorFlow
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
YSDA course in Natural Language Processing
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Code for Tensorflow Machine Learning Cookbook
Notebooks for learning deep learning
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.
The 3rd edition of course.fast.ai
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
PyTorch implementation of AnimeGANv2
Probabilistic reasoning and statistical analysis in TensorFlow
Microsoft Quantum Development Kit Samples
Jupyter notebooks for the Natural Language Processing with Transformers book
A Code-First Introduction to NLP course
A complete course for learning Bitcoin programming and usage from the command
All course materials for the Zero to Mastery Machine Learning and Data Science course.
SDK for interacting with stability.ai APIs (e.g. stable diffusion inference)