The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

12 Weeks, 24 Lessons, AI for All!

Google Research

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 ;)

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

Jupyter Interactive Notebook

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

PyTorch code and models for the DINOv2 self-supervised learning method.

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.

Recipes for using Python's pandas library

AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

A clear, concise, simple yet powerful and efficient API for deep learning.

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn