Data Mining | Machine Learning | Big Data Processing

Stanford University

Explore data mining and machine learning algorithms for analyzing large-scale data using MapReduce and Spark. Gain hands-on experience in data science and big data analysis.

University CoursesMachine LearningMapReduceSpark

Introduction

The course will discuss data mining and machine learning algorithms for analyzing very large amounts of data. The emphasis will be on MapReduce and Spark as tools for creating parallel algorithms that can process very large amounts of data.

screenshot

Highlights

  • Focus on data mining and machine learning algorithms for analyzing large-scale data
  • Emphasis on MapReduce and Spark as tools for parallel data processing
  • Covers a wide range of topics, including frequent itemsets, near neighbor search, dimensionality reduction, recommendation systems, and more

Recommendation

This course is recommended for students with a strong background in computer science, including knowledge of Java, Python, probability theory, linear algebra, and algorithmic analysis. It provides valuable hands-on experience with large-scale data processing and analysis techniques, making it a great choice for those interested in data science, machine learning, and big data.

How GetVM Works

Learn by Doing from Your Browser Sidebar

Access from Browser Sidebar

Access from Browser Sidebar

Simply install the browser extension and click to launch GetVM directly from your sidebar.

Select Your Playground

Select Your Playground

Choose your OS, IDE, or app from our playground library and launch it instantly.

Learn and Practice Side-by-Side

Learn and Practice Side-by-Side

Practice within the VM while following tutorials or videos side-by-side. Save your work with Pro for easy continuity.

Explore Similar Hands-on Tutorials

Getting Started with Artificial Intelligence , 2nd Edition

25
Technical TutorialsData ScienceMachine Learning
Comprehensive introduction to AI, covering machine learning and data science. Practical guide to building enterprise applications with real-world examples.

Machine Learning For Dummies, IBM Limited Edition

19
Technical TutorialsData ScienceMachine Learning
Comprehensive guide to machine learning and data science, suitable for beginners and experienced professionals. Authored by experts Daniel Kirsch and Judith Hurwitz.

Data Mining Concepts and Techniques

25
Technical TutorialsData ScienceMachine Learning
Comprehensive coverage of data mining concepts and techniques, including data preprocessing, classification, clustering, and association rule mining. Essential resource for students, researchers, and professionals in data mining, machine learning, and data analysis.

A Brief Introduction to Machine Learning for Engineers

29
Technical TutorialsMachine Learning
Gain a solid understanding of machine learning concepts and techniques for engineers. Covers supervised, unsupervised, probabilistic models, and advanced topics.

A Comprehensive Guide to Machine Learning

24
Technical TutorialsData ScienceMachine Learning
Detailed resource on machine learning, data science, and artificial intelligence. Authored by experienced experts, suitable for beginners and experienced learners.

A First Encounter with Machine Learning

2
Technical TutorialsData ScienceMachine Learning
Explore fundamental machine learning concepts, algorithms, and applications in data science. Suitable for beginners interested in learning about this rapidly growing field.

A Selective Overview of Deep Learning

3
Technical TutorialsDeep LearningMachine LearningNeural Networks
Comprehensive overview of key concepts and recent advancements in deep learning, covering neural network models, training techniques, and theoretical foundations.

Algorithms for Reinforcement Learning

6
Technical TutorialsMachine LearningReinforcement Learning
Comprehensive guide to reinforcement learning algorithms, covering dynamic programming, temporal difference, Monte-Carlo methods, and more. Suitable for researchers, students, and practitioners in AI, ML, and control engineering.

Approaching Almost Any Machine Learning Problem

8
Technical TutorialsMachine LearningPython
Comprehensive guide to problem-solving approaches in machine learning, suitable for beginners and experienced practitioners. Covers a wide range of ML topics and techniques.