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Working with big data
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Working with big data
Lesson 4: Working with Machine Learning Algorithms
Introduction
Lesson 1: Unstructured Storage and Hadoop
Lesson 2: Structured Storage and Cassandra
Lesson 3: Real Time Processing and Messaging
Lesson 4: Working with Machine Learning Algorithms
Lesson 5: Experimentation and Running Algorithms in Production
Lesson 6: Basic Visualizations
Lesson 4: Working with Machine Learning Algorithms
4.1. Learning objectives
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4.2. Grasp the concepts of machine learning and implement the k-nearest neighbors algorithm
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4.3 Understand the basics of distance metrics and implement euclidean distance and cosine similarity
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4.4. Transform raw data into a matrix and convert a text document into the vector space model
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4.5. Use k-nearest neighbors to make predictions
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4.6. Improve execution time by reducing the search space
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Lesson 3: Real Time Processing and Messaging
Lesson 5: Experimentation and Running Algorithms in Production
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Working with big data
Introduction
Lesson 1: Unstructured Storage and Hadoop
Lesson 2: Structured Storage and Cassandra
Lesson 3: Real Time Processing and Messaging
Lesson 4: Working with Machine Learning Algorithms
Lesson 5: Experimentation and Running Algorithms in Production
Lesson 6: Basic Visualizations
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