Statistical Learning Theory Courses and Certifications

Mathemaniac

Deep Dive into Combinatorics

Explore advanced combinatorics beyond school curriculum, covering Catalan numbers, their generalizations, and mathematical research thinking processes.

• YouTube
• 54 minutes
• Self-Paced
• Free Video

Institute for Advanced Study

Theory of Deep Learning - Where Next?

Explore cutting-edge theoretical foundations of deep learning through expert talks on optimization, generalization, representation learning, and neural network interpretability.

• YouTube
• 17 hours 49 minutes
• Self-Paced
• Free Video

Insights into Mathematics

Real Numbers and Limits

Explore fundamental concepts of real numbers, limits, and mathematical foundations through critical examination of infinity, sequences, and numerical approximation methods.

• YouTube
• 17 hours 19 minutes
• Self-Paced
• Free Video

Pascal Poupart

Introduction to Machine Learning - Spring 2019 - University of Waterloo

Dive into comprehensive machine learning fundamentals covering neural networks, SVMs, deep learning, CNNs, transformers, and ensemble methods from University of Waterloo.

• YouTube
• 1 day 4 hours 26 minutes
• Self-Paced
• Free Video

Richard McElreath

Statistical Rethinking 2022

Master Bayesian inference, multilevel modeling, and causal reasoning through practical statistical methods that avoid common pitfalls in data analysis and research design.

• YouTube
• 1 day 46 minutes
• Self-Paced
• Free Video

Gradient Boost

Explore the fundamentals and advanced concepts of Gradient Boost for regression and classification in machine learning.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video

Learning To See

In this series, we'll explore the complex landscape of machine learning and artificial intelligence through one example from the field of computer vision: using a decision tree to count the number of fingers in an image. It's gonna be crazy.

• YouTube
• 2 hours 30 minutes
• Self-Paced
• Free Video

Reinforcement Learning Course

Comprehensive exploration of reinforcement learning concepts, from basics to advanced topics, including deep RL, policy gradients, and practical applications in classic games.

• YouTube
• 17 hours
• Self-Paced
• Free Video

AssemblyAI

Deep Learning Explained

Discover neural networks, transformers, and NLP fundamentals through comprehensive tutorials covering backpropagation, regularization, RNNs, and modern LLM techniques.

• YouTube
• 3 hours 11 minutes
• Self-Paced
• Free Video

CodeEmporium

The Math You Should Know for Machine Learning

Master essential mathematical concepts for machine learning including probability, linear regression, PCA, gradient descent, and neural network backpropagation.

• YouTube
• 4 hours 53 minutes
• Self-Paced
• Free Video

Andrej Karpathy

Building Makemore - MLP

Implement a multilayer perceptron character-level language model, covering machine learning basics like model training, hyperparameter tuning, evaluation, and addressing under/overfitting.

• YouTube
• 1 hour 16 minutes
• Self-Paced
• Free Video

Tech with Tim

Python Neural Networks - Tensorflow 2.0 Tutorial - What Is a Neural Network?

Explore neural networks using TensorFlow 2.0, covering key concepts, architecture, and practical implementation in Python for beginners and intermediate learners.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Yannic Kilcher

An Image is Worth 16x16 Words - Transformers for Image Recognition at Scale

Explore how Transformers outperform CNNs in image recognition, delving into Vision Transformer architecture, experimental results, and implications for AI research.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Aladdin Persson

YOLOv1 from Scratch

Comprehensive tutorial on implementing YOLOv1 from scratch, covering architecture, loss function, dataset preparation, training, and evaluation for object detection.

• YouTube
• 1 hour 43 minutes
• Self-Paced
• Free Video

StatQuest with Josh Starmer

Regression Trees, Clearly Explained

Clear explanation of regression trees, their applications, and step-by-step construction process. Covers differences from classification trees and use with multiple variables.

• YouTube
• 23 minutes
• Self-Paced
• Free Video