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This is the Seaborn cheat sheet I made to go along with my Seaborn Tutorial Series
The fundamental package for scientific computing with Python.
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
Graph Neural Network Library for PyTorch
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Automated Machine Learning with scikit-learn
Jupyter notebooks from the scikit-learn video series
scikit-learn: machine learning in Python
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
PyTorch Tutorial for Deep Learning Researchers
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Deep Learning Zero to All - Pytorch
Keras documentation, hosted live at keras.io
Keras implementations of Generative Adversarial Networks.
Practice your pandas skills!
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Java implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
Packer configuration for building a custom EKS AMI
A List of frequently asked questions in Amazon's Online Assessment and Interviews
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models
Objective-c code Apple style documentation set generator.
📓 Moved to redhat.gov - OpenShift 3 workshops