Data Mining | Machine Learning | Big Data Processing

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.

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.