A hands-on textbook teaching how to carry out large-scale data analytics and implement machine learning solutions for big data. Including copious real-world examples, it offers a coherent teaching package with lab assignments, exercises, solutions for instructors, and lecture slides.
A hands-on textbook teaching how to carry out large-scale data analytics and implement machine learning solutions for big data. Including copious real-world examples, it offers a coherent teaching package with lab assignments, exercises, solutions for instructors, and lecture slides.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Isaac Triguero is Distinguished Senior Researcher at the Department of Computer Science and Artificial Intelligence, University of Granada, and Associate Professor of Data Science at the School of Computer Science of the University of Nottingham. He won the 2019 School of Computer Science - University of Nottingham Award for Teaching.
Inhaltsangabe
Part I. Understanding and Dealing with Big Data: 1. Introduction 2. MapReduce Part II. Big Data Frameworks: 3. Hadoop 4. Spark 5. Spark SQL and DataFrames Part III. Machine Learning for Big Data: 6. Machine Learning with Spark 7. Machine Learning for Big Data 8. Implementing Classical Methods: k-means and Linear Regression 9. Advanced Examples: Semi-supervised, Ensembles, Deep Learning Model Deployment.
Part I. Understanding and Dealing with Big Data: 1. Introduction 2. MapReduce Part II. Big Data Frameworks: 3. Hadoop 4. Spark 5. Spark SQL and DataFrames Part III. Machine Learning for Big Data: 6. Machine Learning with Spark 7. Machine Learning for Big Data 8. Implementing Classical Methods: k-means and Linear Regression 9. Advanced Examples: Semi-supervised, Ensembles, Deep Learning Model Deployment.
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