Can quantum computers break the speed of information?

GRPO - Group Relative Policy Optimization - How DeepSeek trains reasoning models

Discrete Dynamical Systems - Eigenvalues and Eigenvectors

Mean, Variance, Skewness, and Kurtosis - Math for ML with Deeplearning.ai

Newton's method for approximating zeros of polynomials - Math for ML with Deeplearning.ai

The Stone-Weierstrass Theorem - How to approximate functions

Keys, Queries, and Values: The celestial mechanics of attention

Universal Approximation Theorem - The Fundamental Building Block of Deep Learning

The Kolmogorov-Arnold Theorem

Kolmogorov-Arnold Networks (KANs) - What are they and how do they work?

What is AdaBoost? Friendly explanation with code!

How do Transformer Models keep track of the order of words? Positional Encoding

Model that won the 2024 Physics Nobel Prize - Hopfield Networks

The Fast Fourier Transform

When is a sequence periodic? The Discrete Fourier Transform will tell us

The Discrete Fourier Transform

State Space Models (SSMs) and Mamba

Direct Preference Optimization (DPO) - How to fine-tune LLMs directly without reinforcement learning

KL Divergence - How to tell how different two distributions are

Why do we divide by n-1 to estimate the variance? A visual tour through Bessel correction

Reinforcement Learning with Human Feedback (RLHF) - How to train and fine-tune Transformer Models

Proximal Policy Optimization (PPO) - How to train Large Language Models

Stable Diffusion - How to build amazing images with AI

What are Transformer Models and how do they work?

The math behind Attention: Keys, Queries, and Values matrices

The Attention Mechanism in Large Language Models

The Binomial and Poisson Distributions

Euler's number, derivatives, and the bank at the end of the universe

Decision trees - A friendly introduction

How do you minimize a function when you can't take derivatives? CMA-ES and PSO

What is Quantum Machine Learning?

Denoising and Variational Autoencoders

Eigenvectors and Generalized Eigenspaces

Thompson sampling, one armed bandits, and the Beta distribution

The Beta distribution in 12 minutes!

A friendly introduction to deep reinforcement learning, Q-networks and policy gradients

The Gini Impurity Index explained in 8 minutes!

The covariance matrix

Gaussian Mixture Models

Singular Value Decomposition (SVD) and Image Compression

ROC (Receiver Operating Characteristic) Curve in 10 minutes!

Generative model that won the 2024 Physics Nobel Prize - Restricted Boltzmann Machines (RBM)

A Friendly Introduction to Generative Adversarial Networks (GANs)

You are much better at math than you think

Training Latent Dirichlet Allocation: Gibbs Sampling (Part 2 of 2)

Latent Dirichlet Allocation (Part 1 of 2)

Book by Luis Serrano - "Grokking Machine Learning" (40% off promo code)

Serrano.Academy - The art of understanding

Naive Bayes classifier: A friendly approach

Math and OCD - My story with the Thue-Morse sequence

Principal Component Analysis (PCA)

Clustering: K-means and Hierarchical

Support Vector Machines (SVMs): A friendly introduction

Logistic Regression and the Perceptron Algorithm: A friendly introduction

Linear Regression: A friendly introduction

How does Netflix recommend movies? Matrix Factorization

Deep Neural Networks - USF Data Science Seminar by Luis Serrano

A friendly introduction to Bayes Theorem and Hidden Markov Models

Shannon Entropy and Information Gain

A friendly introduction to Recurrent Neural Networks