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.
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.
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