Machine Learning TV
This channel is all about machine learning (ML). It contains all the useful resources which help ML lovers and computer science students gain a better understanding of the concepts of this successful branch of Artificial Intelligence.
Understanding Tiny Hierarchical Reasoning Models
Инструкция по настройке с обнимающим лицом
Leetcode - 53. Maximum Subarray
Limitations of the ChatGPT and LLMs - Part 3
Understanding ChatGPT and LLMs from Scratch - Part 2
Understanding ChatGPT and LLMs from Scratch - Part 1
Understanding BERT Embeddings and How to Generate them in SageMaker
Understanding Coordinate Descent
Bootstrap and Monte Carlo Methods
Maximum Likelihood as Minimizing KL Divergence
Understanding The Shapley Value
Kalman Filter - Part 2
Фильтр Калмана — Часть 1
Recurrent Neural Networks (RNNs) and Vanishing Gradients
Трансформеры против рекуррентных нейронных сетей (RNN)!
Оценка языковой модели и недоумение
Распространенные закономерности во временных рядах: сезонность, тренд и автокорреляция
Limitations of Graph Neural Networks (Stanford University)
Понимание алгоритма Метрополиса-Гастингса
Learning to learn: An Introduction to Meta Learning
Page Ranking: Web as a Graph (Stanford University 2019)
Deep Graph Generative Models (Stanford University - 2019)
Graph Node Embedding Algorithms (Stanford - Fall 2019)
Graph Representation Learning (Stanford university)
Understanding Word Embeddings
Variational Autoencoders - Part 2 ( Modeling a Distribution of Images )
Variational Autoencoders - Part 1 (Scaling Variational Inference & Unbiased estimates)
DBSCAN: Part 2
DBSCAN: Часть 1
Модели гауссовой смеси для кластеризации