Scala: Applied Machine Learning. Master the art of Machine Learning in Scala
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- Packt Publishing
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książki
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Scala: Applied Machine Learning. Master the art of Machine Learning in Scala
Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions.
The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial.
The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees.
By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala.
This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:
? Scala for Data Science, Pascal Bugnion
? Scala for Machine Learning, Patrick Nicolas
? Mastering Scala Machine Learning, Alex Kozlov
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Patrick R. Nicolas, Alex Kozlov, Pascal Bugnion - pozostałe książki
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Scala is becoming the language of choice for software engineers and data scientists who analyze large data sets. This trend has been reinforced by the wide acceptance of Scala based frameworks such as Apache Spark and Kafka. As a functional language, Scala is particularly suited for extracting knowledge through supervised, unsupervised or reinforcement learning techniques. Being object-oriented, Scala ensured the construction of robust and maintainable software solutions. This book introduces the most common used machine learning models as implemented in Scala-
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Since the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market. One such technology is Scala, which is considered to be a successor to Java in the area of Big Data by many, like Java was to C/C++ in the area of distributed programing. This book aims to take your knowledge to next level-
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Scala is especially good for analyzing large sets of data as the scale of the task doesn’t have any significant impact on performance. Scala’s powerful functional libraries can interact with databases and build scalable frameworks — resulting in the creation of robust data pipelines. The first module introduces you to Scala libraries to ingest, sto-
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Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performan-
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Szczegóły książki
- Tytuł oryginału:
- Scala: Applied Machine Learning. Master the art of Machine Learning in Scala
- ISBN Ebooka:
- 978-17-871-2664-0, 9781787126640
- Data wydania ebooka :
-
2017-02-23
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- Rozmiar pliku Pdf:
- 10MB
- Rozmiar pliku ePub:
- 20.1MB
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