Tutorials Index

Welcome to the Tutorials section! Here, you’ll find step-by-step guides to help you learn and implement various machine learning techniques and algorithms using our tools. Browse through the list of tutorials below and get started on your learning journey!

Table of Contents

  1. CCO LastFM Recommendation
  2. Eigenfaces
  3. Map-Reduce
  4. Miscellaneous
  5. Samsara

CCO LastFM Recommendation

Learn how to build a music recommendation system using Collaborative-Content-Based Filtering (CCO) on LastFM dataset. This tutorial covers data preprocessing, model training, and evaluation.


Discover the Eigenfaces algorithm for face recognition, including steps for preprocessing image data, computing eigenvectors and eigenvalues, and recognizing faces using Principal Component Analysis (PCA).


Get hands-on experience with the Map-Reduce programming model for distributed data processing. This tutorial explains the core concepts, provides examples, and guides you through implementing a custom Map-Reduce job.


Explore a collection of miscellaneous tutorials covering various topics, such as data cleaning, feature engineering, and model optimization techniques.


Dive into Samsara, a vector math experimentation environment with R-like syntax. This tutorial introduces the Samsara environment, its features, and how to use it for linear algebra and machine learning tasks.