100 Things an AI Engineer Should Know
100 Things an AI Engineer Should Know Foundations Python programming Data structures and algorithms Linear algebra Probability theory Statistics Calculus basics Optimization concepts Matrix operations Vector spaces Numerical computing Programming & Software Engineering Object-oriented programming Functional programming basics Git and version control Linux command line Shell scripting APIs and REST JSON and YAML Debugging skills Unit testing Software design principles Python Ecosystem NumPy Pandas Matplotlib Scikit-learn Jupyter notebooks Virtual environments Pip and package management Async programming Logging Type hints Machine Learning Basics Supervised learning Unsupervised learning Reinforcement learning Classification Regression Clustering Dimensionality reduction Feature engineering Cross-validation Bias-variance tradeoff Deep Learning Neural networks Backpropagation Grad...