I’ve recently begun learning about data science and machine learning.
Here are some resources that I found (sorted alphabetically):
- A Lightning-Fast Introduction To Deep Learning And Tensorflow 2.0
- An Introduction to Statistical Learning
- Awesome Data Science
- Awesome ML Ops
- Awesome Machine Learning and AI Courses
- Awesome Machine Learning
- Become A Better Data Egineer on a Shoestring (More Free Resources)
- Building Machine Learning Pipelines
- Chris Albon’s Notes
- Coursera Mathematics for Machine Learning
- Daniel Bourke’s Resources and his AI Masters Degree
- Data Science from Scratch: First Principles with Python
- Deploying and Hosting a Machine Learning Model with FastAPI and Heroku
- End to End Machine Learning Tutorial — From Data Collection to Deployment 🚀
- Full Stack Deep Learning: how to deploy models
- Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- Khan Academy: Math
- Learning Math for Machine Learning
- MIT Deep Learning Book
- ML For Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
- ML Ops
- ML from the Fundamentals
- Machine Learning Algorithms from Scratch in Python
- Machine Learning Engineering book
- Machine Learning Glossary
- Machine Learning Mastery: Start Here
- Machine Learning Simplified free online ebook
- Machine Learning from Scratch: covers the building blocks of the most common methods in machine learning
- Mathematics For Machine Learning
- Mathematics for the adventurous self-learner
- Neural Networks and Deep Learning
- Putting ML in Production: a guide and code-driven case study on MLOps for software engineers, data scientists and product managers
- Python Data Science Handbook
- Resources for learning numpy, pandas, etc. (applying deep learning is goal)?
- Statistics 101
- The Elements of Statistical Learning
- The Hundred-Page Machine Learning Book
- The Incredible Pytorch: a curated list of tutorials, projects, etc. for PyTorch
- Think Stats 2e
- Udemy: Complete Machine Learning and Data Science: Zero to Mastery
- fast.ai course and fast.ai book: Practical Deep Learning for Coders with fastai and PyTorch
- r/datascience Resources
- r/learnmachinelearning Resources
- r/learnmachinelearning: List of Machine Learning Resources for a Beginner
Videos
- The Machine Learning Engineer Roadmap 💻🤖 | How to become a Machine Learning Engineer in 2020 (diagram here)
- The Ultimate FREE Machine Learning Study Plan
- Data Science Crash Course
- Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)
- TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners
- Applied Deep Learning with PyTorch - Full Course (from 2019)
- Deep Learning with PyTorch - Full Course (from 2020)
- Matplotlib Crash Course
- Scikit-Learn Course - Machine Learning in Python Tutorial
- Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial
- Deep Learning Crash Course - Learn the key concepts and terms
- Statistics for Data Science & Machine Learning
- NumPy Tutorial 2020
- Pandas Tutorial 2020
- Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard
- freeCodeCamp.org Curriculum Expansion: Math + Machine Learning + Data Science
- Data Analysis with Python Course - Numpy, Pandas, Data Visualization
- Build A Machine Learning Web App From Scratch
- Scikit-learn Crash Course - Machine Learning Library for Python
