Machine learning

Lec 4: Logistics Regression

Lec 2: Supervised Learning (Regression)

Lec 1: Introduction to Learning

West Coast ML State of AI - Part 2

Meta annonce LA FIN de l'ère ChatGPT (Y. Lecun avait raison)

Meta announces THE END of the ChatGPT era (Y. Lecun was right)

Irit Chelly - Consistent Amortized Clustering via Generative Flow Networks (Heb)

Hands-on Machine Learning -- Custom Models and Training with TensorFlow

AutoGrad Changed Everything (Not Transformers) [Dr. Jeff Beck]

MACLA memoria y aprendizaje continuo, Transferencia humano-robot, Problema y dato del problema

MACLA memory and continuous learning, human-robot transfer, problem and problem data

Bringing Your App to Life with Vertex AI and Cloud Run

Construire un RAG avec Chat GPT 5.2| Comprendre les embeddings & les PDF !

Step-by-Step RAG Setup | Vectors and Embeddings Explained GPT5.2

Модель кластеризации DBSCAN простыми словами | МАШИННОЕ ОБУЧЕНИЕ

DBSCAN Clustering Model in Simple Terms | Machine Learning

Ce RAG 2.0 SURPERFORME tous les autres (Workflow n8n GRATUIT)

This RAG 2.0 OUTPERFORMS all others (FREE n8n workflow)

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 14: Байесовская оптимизация

[IAD, Fall 2025] Bayesian Model Selection. Lecture 14: Bayesian Optimization

The "Final Boss" of Deep Learning

MLT - Revision session 2_End term

MLP 25T3 EndTerm Revision

L12 Unsupervised Learning K Means Clustering

L11 Classification Performance Metrics

VLA Models and the New Robotics

MLT - Revision session 1_End term

Inbar Seroussi - SGD Exact Dynamics in High-Dimension: Insights for Algorithm Design (Eng)

Exhaustive Symbolic Regression, or how to find the best function for your data

RL en pre-training, Subespacios universales en DNNs, Unsupervised Learning

RL in pre-training, Universal subspaces in DNNs, Unsupervised Learning

Keynote Address - Engineering Intelligence: Building Practical ML Systems

NeurIPS Summary and ML News

MLT - Week 11, 12 SWU

L10 Nonlinear & Multiclass Classification

Tony Jebara: Discriminative Learning of Generative Models

Tong Zhang: Two Algorithms for Learning Sparse Representations

Lawrence K. Saul: Distance Metric Learning for Large Margin Classification

Jason Eisner: Hidden Markov Models

Dale Schuurmans: Convex Training Algorithms for Hard Machine Learning Problems

Corinna Cortes: Rational Kernels: A General Machine Learning Framework for the Analysis of Text,...

Zohar Ringel - A Heuristic for Feature Learning and Sample Complexity (Heb)

The Mathematical Foundations of Intelligence [Professor Yi Ma]

MLT - Week 12

L9 Classification (Logistic Regression)

Building Synthetic Data Pipelines for Open Research and Scalable AI Development

PINN for Challenging Multiphase Flow Problems||Multi-Agent LLM for Intelligent Design ||Dec 12, 2025