This article represents information on Big Data initiative from MIT (Massachusetts Institute of Technology) including bookmarks on lecture notes related machine learning courses and also, machine learning video channel from MIT on Youtube. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos.
Following are the key points described later in this article:
- MIT CSAIL Big Data Initiative
- Machine Learning Lecture Notes & Videos
MIT CSAIL Big Data Initiative
MIT has a website dedicated to Big Data initiative from MIT CSAIL (Computer Science and Artificial Intelligence Laboratory). Following pages are worth visits to understand ongoing research and listen/view talks that happened in past.
MIT Machine Learning Lecture Notes & Videos
Following are worth bookmarks for some of the online courses provided by MIT education community (Lecturers and Professors)
- How to Process, Analyze and Visualize Data: This course is an introduction to data cleaning, analysis and visualization. Following are some of the key topics taught as part of this course:
- Visualization
- Hypothesis testing
- Regression
- Text processing
- Prcoessing large datasets
- Lectures on Machine Learning: The page consists of PDFs on different machine learning concepts. Following are three key machine learning topics that have been detailed along with different algorithms:
- Regression
- Classification
- Clustering
- Machine Learning and Statistics: There are lecture notes on some of the following:
- Clustering
- Classification (k-nearest neighbors, Naïve Bayes, Decision trees, Logistic regression, Support vector machines)
- Boosting
- Videos on Machine Learning Topics: Following are some of the videos I liked:
Latest posts by Ajitesh Kumar (see all)
- Agentic Reasoning Design Patterns in AI: Examples - October 18, 2024
- LLMs for Adaptive Learning & Personalized Education - October 8, 2024
- Sparse Mixture of Experts (MoE) Models: Examples - October 6, 2024
I found it very helpful. However the differences are not too understandable for me