Using Data Science to Fight Covid-19 and How to Start Learning ADSB
Explore data science applications in fighting COVID-19, learn about pandemics, and discover pathways to start a data science career with insights from MIT faculty and industry experts.
Machine Learning Full Course for Beginners
Comprehensive introduction to machine learning, covering key concepts, algorithms, and practical applications using Python libraries. Ideal for beginners seeking a solid foundation in ML.
Machine Learning Crash Course With ML.NET
Comprehensive introduction to machine learning concepts and hands-on demonstration using ML.NET, covering key processes from data loading to model evaluation with practical C# examples.
What Is Machine Learning Anyway?
Explore the fundamentals of machine learning, its applications in microscopy, and different types including supervised and unsupervised learning.
How K-Nearest Neighbors Works
Explore k-nearest neighbors algorithm for classification and regression, including key considerations like k value, feature scaling, and distance metrics.
Ultimate Machine Learning Projects with Python for Beginners - 2024
Master Python-based machine learning through hands-on projects, from basic algorithms to advanced applications like fake news detection, predictive maintenance, and emotion recognition. Build a portfolio with real-world implementations.
Machine learning en espanol
Introducción práctica al aprendizaje automático en español, cubriendo técnicas supervisadas y no supervisadas con aplicaciones reales como reconocimiento de imágenes y sistemas de recomendación.
Machine Learning Tutorials for Beginners Using Python in Hindi
हिंदी में पायथन का उपयोग करके मशीन लर्निंग की मूल बातें सीखें। लीनियर रिग्रेशन, सपोर्ट वेक्टर मशीन और डिसीजन ट्री जैसी तकनीकों को समझें और कोड करें।
Linear Regression in Machine Learning - Machine Learning Tutorial
Comprehensive exploration of linear regression in machine learning, covering key concepts, applications, and implementation in Python. Ideal for beginners seeking practical understanding of predictive modeling.
Introduction to Reinforcement Learning - Lecture 1: Overview of RL
强化学习入门概述:介绍RL基本概念、特点和应用,探讨其与监督学习的区别,展示RL在游戏、机器人等领域的成功案例,解释RL与深度学习的结合。
Demystifying AI - Understanding Machine Learning Fundamentals
Fundierte Einführung in Künstliche Intelligenz: Grundlagen des maschinellen Lernens, mathematische Konzepte und Herausforderungen werden verständlich erklärt. Praktische Tipps für den Einstieg inklusive.
Veri Biliminin Derinlerine Yolculuk - Geleceğin Haritası
Veri biliminin toplumsal etkileri, makine öğrenmesinin günlük hayattaki uygulamaları ve kişisel deneyimler üzerinden alanın geleceğine dair ilham verici bir bakış.
Complete Machine Learning Course - From Basics to Advanced Concepts
Comprehensive Hindi guide covering ML fundamentals, supervised/unsupervised learning, reinforcement, ensemble methods, neural networks, and genetic algorithms for exam preparation.
Introduction to the Dynamics of Disordered Systems: Equilibrium and Gradient Descent - Lecture 1
Explore disordered systems dynamics, covering glasses, jamming transitions, and optimization problems. Gain insights into metastable states and algorithmic applications in various fields.
Beyond Bias Audits: Bringing Equity to the Machine Learning Pipeline
Explorez les approches pour intégrer l'équité dans l'apprentissage automatique appliqué aux soins de santé, en abordant les biais algorithmiques et les disparités en matière de santé.
Введение в машинное обучение - Часть V
Изучите основы машинного обучения, включая ключевые концепции и методы, для развития навыков в этой перспективной области информационных технологий.
Robotics Seminar - Michael Beetz - University Bremen, IAI
Explore cognitive architectures and knowledge representation for advanced robot manipulation, focusing on symbolic reasoning, mental simulation, and real-world applications in autonomous systems.
Targeting Crimes and Criminals Through Data - Dr. Rick Adderley
Explore data mining in law enforcement, covering challenges in police data analysis, criminal network analysis, and advanced analytics for crime prevention and resource optimization.
A Number Sense as an Emergent Property of the Manipulation Brain
Explore how number sense emerges from brain manipulation, examining experiments, perceptions, and the role of supervised learning in developing numerical understanding.
Robots Learning Through Interaction
Explore robot learning through interaction, covering supervised, imitation, reinforcement, and interactive learning methods. Gain insights into motor skill acquisition and human-robot collaboration.
Towards Large Behavior Models: Versatile and Dexterous Robots via Supervised Learning
Explore advancements in machine learning for robotics, focusing on creating versatile and dexterous robots through supervised learning and the development of Large Behavior Models.