rasbt / machine-learning-notesLinks
Collection of useful machine learning codes and snippets (originally intended for my personal use)
☆835Updated last year
Alternatives and similar repositories for machine-learning-notes
Users that are interested in machine-learning-notes are comparing it to the libraries listed below
Sorting:
- Deep Learning Fundamentals -- Code material and exercises☆400Updated last year
- ☆602Updated 2 years ago
- A curated list of awesome fastai projects/blog posts/tutorials/etc.☆173Updated 4 years ago
- 🧠 A study guide to learn about Transformers☆1,628Updated 2 years ago
- Educational materials on deep learning by Weights & Biases☆662Updated last year
- ☆151Updated 4 years ago
- ☆295Updated 2 years ago
- Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning☆348Updated 4 years ago
- Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-…☆493Updated 2 years ago
- Kaggle Pipeline for tabular data competitions☆205Updated this week
- Compilation of high-profile real-world examples of failed machine learning projects☆746Updated last year
- STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)☆539Updated 4 years ago
- Host repository for the "Reproducible Deep Learning" PhD course☆408Updated 3 years ago
- Interpretable Machine Learning with Python, published by Packt☆475Updated this week
- Lightning Bits: Engineering for Researchers repo☆134Updated 3 years ago
- Set up your local environment to do some real Machine Learning Operations software development, just like pro MLOps practitioners.☆242Updated 2 years ago
- Machine Learning for Imbalanced Data, published by Packt☆277Updated last month
- Applied Machine Learning Explainability Techniques, published by Packt☆248Updated last month
- GitHub Repo with various ML/AI/DS resources that I find useful☆468Updated last year
- AI-related tutorials. Access any of them for free → https://towardsai.net/editorial☆1,012Updated last year
- Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.☆1,239Updated 2 years ago
- Lab assignments for Introduction to Data-Centric AI, MIT IAP 2024 👩🏽💻☆479Updated 11 months ago
- Revisions and implementations of modern Convolutional Neural Networks architectures in TensorFlow and Keras☆358Updated 3 years ago
- Software Architecture for ML engineers☆416Updated 3 years ago
- Teaching materials for the applied machine learning course at Cornell Tech (online edition)☆1,172Updated 3 years ago
- All about the fundamental blocks of TF and JAX!☆277Updated 4 years ago
- Practical Deep Learning at Scale with MLFlow, published by Packt☆163Updated last month
- Examples of python neural net and ML stock prediction methods with sample stock data.☆271Updated last year
- Supplementary Materials for the Deep Learning Book by Ian Goodfellow et al☆54Updated 3 years ago
- Setup PyTorch on Mac/Apple Silicon plus a few benchmarks.☆437Updated 2 years ago