4-machine-learning-engineer

Machine Learning Engineer

This job is to build and deploy smart products that automate tasks. To do this, we care more about prediction accuracy than traditional statistics. This role is more computer scientist than statistician. They train/teach machines to independently perform various useful tasks that are typically low impact but high quantity.

Library Recommendations

• MUST READ! - Python Data Science Handbook
• MUST READ! - Statistical Modeling: The Two Cultures
• Basic - Automate the Boring Stuff with Python
• ML Specific practical - Hands On Machine Learning with scikitlearn, Keras, & Tensorflow
• ML Specific practical - Machine Learning with Pytorch and Scikit-Learn
• ML Specific advanced - Pattern Recognition and Machine Learning - Book
• ML Specific advanced - Pattern Recognition and Machine Learning - Repo

Cheatsheets

• Python3 Cheatsheet
• Stanford - ML Cheatsheet
• Numpy
• Pandas
• Matplotlib

Python

• Hands On Machine Learning
• Calmcode
• Python Books
• The Algorithms - Python
• Kats - Time Series

Math

• Mathematics for Machine Learning
• Matrix Calculus for Deep Learning
• Pen and Paper Machine Learning Problems
• Calculus Made Easy

Deployment

• Command Line - Bash Manual
• Docker
• AWS - ML

Deep Learning

• Start here to build ML products fast - Fast.AI
• Or start here to understand concepts at a detailed level :) Andrew Ng's ML and Deeplearning Courses
• Intro to Deep Learning - Sebastian Raschka
• Pytorch Image Models
• Deep Learning Paper Implementations
• Google - Deep Learning Tuning Playbook
• Confetti AI
• NVIDIA Deep Learning Institute
• Awesome Data Labeling
• Deep Learning Demystified
• ONNX
• MIT - Deep Learning

Interesting Deep Learning Projects

• MusicML - create music from a test prompt

Other

• Human Learn
• REGEX
• MIT - Missing Semester of CS
• Hidden Technical Debt in ML Systems
• Open Source Computer ScienceFrom-0-to-Research-Scientist-resources-guide)
• UMW - Intro to Machine Learning
• CMU - Machine Learning at Scale
• Stanford - Machine Learning Systems Design
• [Zero to Research Scientist](https://github.com/ahmedbahaaeldin/
• Intro to Kalman Filter
• Metaflow - data science project management
• Interpretable Machine Learning
• Gitlab Data Engineering Handbook
• MLOps is a Mess
• Designing Machine Learning Systems
• Learning Path for ML Engineer
• MIT - Intro to Computational Thinking and Data Science
• Machine Learning from Scratch
• AWS ML Courses
• [Free Books](https://www.theinsaneapp.com
• ML From Scratch