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Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations.
What You Will Learn
Be introduced to machine learning, Spark, and Spark MLlib 2.4.x
Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries
Detect anomalies with the Isolation Forest algorithm for Spark
Use the Spark NLP and Stanford CoreNLP libraries that support multiple languages
Optimize your ML workload with the Alluxio in-memory data accelerator for Spark
Use GraphX and GraphFrames for Graph Analysis
Perform image recognition using convolutional neural networks
Utilize the Keras framework and distributed deep learning libraries with Spark
Who This Book Is For
Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.
Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations.
What You Will Learn
Be introduced to machine learning, Spark, and Spark MLlib 2.4.x
Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries
Detect anomalies with the Isolation Forest algorithm for Spark
Use the Spark NLP and Stanford CoreNLP libraries that support multiple languages
Optimize your ML workload with the Alluxio in-memory data accelerator for Spark
Use GraphX and GraphFrames for Graph Analysis
Perform image recognition using convolutional neural networks
Utilize the Keras framework and distributed deep learning libraries with Spark
Who This Book Is For
Data scientists and machine learning engineers who want to take their knowledge to the next level and use Spark and more powerful, next-generation algorithms and libraries beyond what is available in the standard Spark MLlib library; also serves as a primer for aspiring data scientists and engineers who need an introduction to machine learning, Spark, and Spark MLlib.
Butch Quinto is founder and Chief AI Officer at Intelvi AI, an artificial intelligence company that develops cutting-edge solutions for the defense, industrial, and transportation industries. As Chief AI Officer, Butch heads strategy, innovation, research, and development. Previously, he was the Director of Artificial Intelligence at a leading technology firm and Chief Data Officer at an AI startup. As Director of Analytics at Deloitte, Butch led the development of several enterprise-grade AI and IoT solutions as well as strategy, business development, and venture capital due diligence. He has more than 20 years of experience in various technology and leadership roles in several industries including banking and finance, telecommunications, government, utilities, transportation, e-commerce, retail, manufacturing, and bioinformatics. Butch is the author of Next-Generation Big Data (Apress) and a member of the Association for the Advancement of Artificial Intelligence andthe American Association for the Advancement of Science.
For the latest version of Spark and Spark MLlib
Covers powerful third-party machine learning algorithms and libraries not available in the standard Spark MLlib library such as XGBoost4J-Spark, LightGBM on Spark, Isolation Forest, Spark NLP, and Stanford CoreNLP
Includes distributed deep learning using convolutional neural networks with Spark and Keras
Chapter 1: Introduction to Machine Learning.- Chapter 2: Introduction to Spark and Spark Mllib.- Chapter 3: Supervised Learning.- Chapter 4: Unsupervised Learning.- Chapter 5: Recommendations.- Chapter 6: Graph Analysis.- Chapter 7: Deep Learning.-
| Erscheinungsjahr: | 2020 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 376 |
| Inhalt: |
xix
355 S. 67 s/w Illustr. 355 p. 67 illus. |
| ISBN-13: | 9781484256688 |
| ISBN-10: | 1484256689 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: | Quinto, Butch |
| Auflage: | 1st ed. |
| Hersteller: | APRESS |
| Maße: | 254 x 178 x 21 mm |
| Von/Mit: | Butch Quinto |
| Erscheinungsdatum: | 23.02.2020 |
| Gewicht: | 0,706 kg |
Butch Quinto is founder and Chief AI Officer at Intelvi AI, an artificial intelligence company that develops cutting-edge solutions for the defense, industrial, and transportation industries. As Chief AI Officer, Butch heads strategy, innovation, research, and development. Previously, he was the Director of Artificial Intelligence at a leading technology firm and Chief Data Officer at an AI startup. As Director of Analytics at Deloitte, Butch led the development of several enterprise-grade AI and IoT solutions as well as strategy, business development, and venture capital due diligence. He has more than 20 years of experience in various technology and leadership roles in several industries including banking and finance, telecommunications, government, utilities, transportation, e-commerce, retail, manufacturing, and bioinformatics. Butch is the author of Next-Generation Big Data (Apress) and a member of the Association for the Advancement of Artificial Intelligence andthe American Association for the Advancement of Science.
For the latest version of Spark and Spark MLlib
Covers powerful third-party machine learning algorithms and libraries not available in the standard Spark MLlib library such as XGBoost4J-Spark, LightGBM on Spark, Isolation Forest, Spark NLP, and Stanford CoreNLP
Includes distributed deep learning using convolutional neural networks with Spark and Keras
Chapter 1: Introduction to Machine Learning.- Chapter 2: Introduction to Spark and Spark Mllib.- Chapter 3: Supervised Learning.- Chapter 4: Unsupervised Learning.- Chapter 5: Recommendations.- Chapter 6: Graph Analysis.- Chapter 7: Deep Learning.-
| Erscheinungsjahr: | 2020 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 376 |
| Inhalt: |
xix
355 S. 67 s/w Illustr. 355 p. 67 illus. |
| ISBN-13: | 9781484256688 |
| ISBN-10: | 1484256689 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: | Quinto, Butch |
| Auflage: | 1st ed. |
| Hersteller: | APRESS |
| Maße: | 254 x 178 x 21 mm |
| Von/Mit: | Butch Quinto |
| Erscheinungsdatum: | 23.02.2020 |
| Gewicht: | 0,706 kg |
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