I'm [Chris](Short%20Bio.md). I am the Director of Machine Learning at the [Wikimedia Foundation](https://wikimediafoundation.org/). Here are my 57 notes on applied artificial intelligence, based on ~34 sources: * **Machine Learning** * [[Training, Test, And Validation Sets]] * [[Reinforcement Learning]] * [[Four Types Of AI]] * [[Dimensionality Reduction]] * [[Feature Scaling]] * [[Clustering]] * [[Regression]] * [[Classification]] * [[Overfitting And Underfitting]] * [[Capacity]] * **Pre-processing data** * [[Mutual Information]] * [[One-hot encoding]] * [[Target encoding]] * **Neural Networks** * [[Stochastic Gradient Descent]] * [[Deep Double Descent]] * [[Internal Covarate Shift]] * [[Learning Rate]] * [[FLOPS]] * [[Vanishing Gradient]] * [[Weight Decay Regularization]] * [[Gradient Descent]] * [[Positional Encoding]] * [[Bias]] * [[Motivation]] * [[Autoencoders]] * [[How Deep Neural Networks Learn]] * [[Batching]] * **Layers** * [[Skip Connections]] * [[Batch Normalization Layer]] * [[Convolutional Layers]] * [[Embedding Layers]] * [[Max Pooling Layer]] * [[Fully Connected Layers]] * [[Dropout Layer]] * **Activation Functions** * [[Gaussian Error Linear Unit (GELU)]] * [[Hyperbolic Tangent (Tanh)]] * [[Rectified Linear Unit (ReLU)]] * [[Leaky ReLU]] * [[What is an activation?]] * [[Motivation]] * **Large Language Models** * [[Fine-Tuning Vs. Training]] * [[History]] * [[Hallucinations]] * **Python** * [[Type Hinting]] * **Object Oriented Programming** * [[Example Of @property]] * [[Abstract Base Classes And Methods]] * [[Difference Between Class And Instance Variables]] * **Three Tenets Of OOP** * [[Polymorphism]] * [[Inheritance]] * [[Encapsulation]] * [[Abstraction]] * **MLOps** * [[Data Warehouse Vs. Data Lake]] * [[Declarative ML Systems]] * [[Data Model]] * **Mathematics** * **Linear Algebra** * [[Broadcasting]] * [[Vector Operations]] * [[Tensors]] * **Probability** * [[Sample Space]] * [[Central Limit Theorem]] * [[Random Variable]] * [[Law Of Large Numbers]] * **Computer Science** * [[Handling Numbers]] * **Data** * [[Extracting Training Data From Models]] * [[MNIST Dataset]] * **Software Engineering** * [[Clean Code]] * [[Concurrency]]