Mastering Spark for Data Science by Andrew Morgan English | 29 Mar. 2017 | ASIN: B01BWNXA82 | 560 Pages | AZW3 | 12.66 MB Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grad
Mastering Java for Data Science by Alexey Grigorev English | 4 May 2017 | ASIN: B01JLBMHMM | 364 Pages | AZW3 | 2.1 MB Key Features An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics
Mastering.Java.for.Data.Science An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamen
Data Science with Java: Practical Methods for Scientists and Engineers by PhD Michael R. Brzustowicz English | 6 Jun. 2017 | ASIN: B072MKRQBQ | 236 Pages | AZW3 | 2.78 MB Data Science is booming thanks to R and Python, but Java brings the robustness
Agile Data Science 2.0: Building Full-Stack Data Analytics Applications with Spark by Russell Jurney English | 7 Jun. 2017 | ASIN: B072MKL34K | 352 Pages | AZW3 | 5.91 MB Data science teams looking to turn research into useful analytics applications
An Introduction to Data Science by Jeffrey S. Saltz and Jeffrey M. Stanton is an easy-to-read, gentle introduction for people with a wide range of backgrounds into the world of data science. Needing no prior coding experience or a deep understanding
Beginning Data Science in R - Data Analysis, Visualization, and Modelling for the Data Scientist Welcome to Introduction to Data Science with R. This book was written as a set of lecture notes for two classes I teach, Data Science: Visualization and
Python has emerged over the last couple decades as a first-class tool for scientific computing tasks, including the analysis and visualization of large datasets. This may have come as a surprise to early proponents of the Python language: the langua
