Machine learning is a branch of artificial intelligence (AI) that gives computers the ability to learn without being explicitly programmed. Machine learning can be used in a wide range of applications, like: computer vision, speech recognition, natural language processing and many others. In this post we provide an overview of machine learning lectures online in order to help you get started with ML or enhance your knowledge if you are already using it.
Machine Learning Video Lectures
The Machine Learning Video Lectures archive contains 10 lectures on the topic of machine learning. The course is available for free on YouTube, but also has a page on Coursera’s website where you can access additional resources and quizzes.
The course is recommended for beginners who have an interest in learning more about how computers learn from data.
Overview of Lectures
This course is about machine learning. It will cover the following topics:
- The basics of probability and statistics, including distributions and hypothesis testing
- Classification algorithms (e.g., decision trees, logistic regression)
- Clustering techniques (k-means clustering)
- Unsupervised learning methods (e.g., principal components analysis, neural networks).
Machine Learning Overview
Machine learning is a subfield of artificial intelligence that focuses on algorithms that can learn from data. Machine learning is about building algorithms that can learn from data, and it’s a very broad term that encompasses many different types of algorithms, including:
- Supervised Learning: When you have both input and output data, machine learning algorithms use this information to make predictions about future examples (for example,