Machine Learning and Deep Learning Courses on YouTube
Explore a curated selection of YouTube courses designed to deepen your understanding of machine learning and deep learning, ranging from foundational concepts to specialized applications in various fields.
Foundational Machine Learning Courses
- Explore the basics of machine learning with the Introduction to Machine Learning (Tübingen), offering insights into regression, classification, and more.
- Dive into Statistical Machine Learning (Tübingen) to understand algorithms and paradigms in statistical learning.
- Grasp the fundamentals with Machine Learning Lecture (Stefan Harmeling), covering key concepts from Bayes’ rule to Gaussian Processes.
- The Caltech CS156: Learning from Data course provides a comprehensive introduction, from the learning problem to support vector machines.
- For practical application, Applied Machine Learning teaches widely used techniques including optimization and regularization.
Deep Learning Exploration
- Begin your deep learning journey with Introduction to Deep Learning (MIT), a fundamental course for beginners.
- The Deep Learning: CS 182 course covers techniques from error analysis to imitation learning.
- Neural Networks: Zero to Hero by Andrej Karpathy provides an in-depth look into neural networks.
- Discover the intersection of creativity and AI with MIT: Deep Learning for Art, Aesthetics, and Creativity.
- Engage with Deep Unsupervised Learning to learn about latent variable models and self-supervised learning techniques.
Specialized Courses in Machine Learning
- For healthcare applications, MIT 6.S897: Machine Learning for Healthcare (2019) introduces ML in clinical contexts.
- The Machine Learning with Graphs (Stanford) course delves into techniques like PageRank and graph neural networks.
- In the realm of NLP, CS224N: Natural Language Processing with Deep Learning offers a comprehensive exploration of deep learning-based NLP.
Practical and Real-World Applications
- Learn about building applications with large language models through LLMOps: Building Real-World Applications With Large Language Models.
- Full Stack Deep Learning teaches how to bring deep learning models into production, covering everything from infrastructure to web deployment.
Exploring Computer Vision and Reinforcement Learning
- Stanford’s CS231N: Convolutional Neural Networks for Visual Recognition is a landmark course for those interested in computer vision.
- Delve into the dynamics of decision-making systems with Reinforcement Learning (Polytechnique Montreal, Fall 2021), covering everything from multi-armed bandits to Monte Carlo methods.
This selection of YouTube courses offers a comprehensive pathway for learners at various stages of their machine learning and deep learning journey, from foundational knowledge to advanced applications and real-world problem-solving.