Machine learning

Fair universe HiggsML Uncertainty challenge - Ragansu CHAKKAPPAI

Bayesian continual learning and forgetting in neural networks - Kellian COTTART

Week 3 - Summary session

Stanford CS230 | Autumn 2025 | Lecture 2: Supervised, Self-Supervised, & Weakly Supervised Learning

Week 2- solve with us

Machine Learning 3 [Odd Semester 2025/2026 Telyu] - Decision Tree & KNN

Sensitivity of ITS Learning Models with Mobility Data

MLP 25T3 W2L2

Eshaan Nichani: Learning Compositional Functions with Transformers from Easy-to-Hard Data

Ekdeep Lubana: In-context Learning of Formal Languages

[ИАД, осень 2025] Вероятностные тематические модели. Лекция 3

[IAD, autumn 2025] Probabilistic topic models. Lecture 3

I Built an AI That Automates My Morning Routine (Using n8n)

Week 2

Jakob Zeitler on Bayesian Optimisation for Materials and Brownies | FAI CDT

[ИАД, осень 2025] Математические методы прогнозирования. Лекция 3

[IAD, Fall 2025] Mathematical Methods of Forecasting. Lecture 3

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 4: Обоснованность (evidence)

[IAD, Fall 2025] Bayesian Model Selection. Lecture 4: Evidence

RL en pretraining, Más emergencia en AI, "Benchmarks" reales

RL in pretraining, More emergency in AI, real benchmarks

MLP25T3 W2L1

Hands-On Machine Learning -- Ensemble Learning, Random Forests, and Gradient Boosting

Scaling Large Language Models: Getting Started with Large-Scale Parallel Training of LLMs

Machine Learning 2 [Odd Semester 2025/2026 Telyu] - The Linear Models

Machine Learning 1 [Odd Semester 2025/2026 Telyu] - Introduction to Machine Learning

MLP_WEEK_1_LIve_Session_2

Hands-On Machine Learning -- Decision Trees

3 Hidden Data Table Hacks for Smarter AI Agents

The New and Improved Way to Build ANYTHING with AI

Reinforcement Learning for LLMs to Enhance Safety

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 3: Байесовская линейная регрессия

[IAD, fall 2025] Bayesian model selection. Lecture 3: Bayesian linear regression

Week 1 - Summary session

MLP 25T3 Live session Week1

[ИАД, осень 2025] Вероятностные тематические модели. Лекция 2

[IAD, Fall 2025] Probabilistic Topic Models. Lecture 2

Créez votre premier AGENT IA en RAG - Tutoriel complet!

Create your first AI AGENT in RAG - Complete Tutorial!

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 2: Наивный Байес, Экспоненциальное семейство

[IAD, fall 2025] Bayesian model selection. Lecture 2: Naive Bayes, Exponential family

Understanding Tokenization in Audio and Speech

The Real Reason Huge AI Models Actually Work [Prof. Andrew Wilson]

The NEW Easiest Way to Build RAG Agents in Minutes (no code)

Hongbo Zhao - Learning Physics of Electrochemical Systems from Data - IPAM at UCLA

Generative Models for Turbulent Flows || Meta Learning PINNs || Sep 19, 2025

[ИАД, осень 2025] Foundation models for spatial-time series. Занятие 2

[IAD, autumn 2025] Foundation models for spatial-time series. Class 2

Day 3- MLT workshop_Sep 25