Machine learning

Machine Learning Practice: Getting Connected to CoLab

Machine Learning Practice: Getting Connected to CoLab

Implementing Data Processing Pipelines

Example: Using Cross Validation

Example: Multi Class Classification

Drift Detection and ML Solution Retraining (4/4)

Drift Detection and ML Solution Retraining (3/4)

Drift detection and ML Solution retraining part (1/4)

(Drift detection and ML Solution retraining part (2/4

Bayesian network revisited

Detecting model drift using polynomial relations

Detecting Concept Drift in the Presence of Sparsity A Case Study of Automated Change Risk

Data dependent priors for domain adaptation bounds

A Unified Perspective on Adversarial and Out of Distribution Detection in the Open World

Lecture 14: MIT 6.832 Underactuated Robotics (Spring 2022) | "Direct Policy Search"

Lecture 6: MIT 6.832 Underactuated Robotics (Spring 2022) | "Dynamic Programming III"

Fourier, Decision Trees, Learning Algorithms || @ CMU || Recitation 5 of CS Theory Toolkit

Solving Wordle using information theory

How can ERM be fooled?

#036 ML Борис Шарчилев. Как пройти собеседование в ML-команду

#036 ML Boris Sharchilev. How to pass an interview for an ML team

Lecture 20: MIT 6.800/6.843 Robotics Manipulation (Fall 2021) | "Reinforcement Learning (Part 3)"

Lecture 19: MIT 6.800/6.843 Robotics Manipulation (Fall 2021) | "How to Train your Robot"

Lecture 18: MIT 6.800/6.843 Robotics Manipulation (Fall 2021) | "Reinforcement Learning (Part 1)"

Using linear regression to estimate non-linear problems (with code!)

Lecture 17: MIT 6.800/6.843 Robotics Manipulation (Fall 2021) | "Behavior Cloning"

#031 ML Алексей Харламов. Как фармить золото с помощью ML на Kaggle

#031 ML Alexey Kharlamov. How to farm gold with ML on Kaggle

Qiskit Falll Fest CIC-IPN Mexico 2021- Introducción al Aprendizaje de Máquina Cuántico

Qiskit Fall Fest CIC-IPN Mexico 2021- Introduction to Quantum Machine Learning

Machine Learning Practice: CoLab Interface

#027 ML Петр Ермаков. ODS - русскоязычное сообщество дата-сайентистов

#027 ML Petr Ermakov. ODS - Russian-speaking data scientist community

reading conditional independence from the BN

#026 ML Виталий Моисеев. Рекомендательные системы - как вырастить "счастье пользователей"

#026 ML Vitaly Moiseev. Recommender systems - how to grow "user happiness"

Gradient Descent | Neural Networks

Backpropagation Algorithm | Neural Networks

Sequential identification of agent reliability and the Bayes factor

#025 ML Про стажировки в Яндексе и распознавание рукописных цифр

#025 ML About internships at Yandex and handwritten digit recognition

Bayesian Networks independence I

Machine Learnia, La suite commence ici.

Machine Learnia, The sequel starts here.

#023 ML Ольга Перепелкина. Про федеративное обучение и распознавание эмоций

#023 ML Olga Perepelkina. About federated learning and emotion recognition

[Extract] The UK's Quantum Computer webinar ::: Alexei Kondratyev - Quantum Machine Learning

VC dimension as an adversary to learning