Julia is a fast and high performing language perfectly suited for data science with a mature package ecosystem, and is now feature-complete. This book will help you get familiarized with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game.
You can dive in and learn the essentials of data science, with practical coverage of statistics and machine learning. You will learn to apply real-world skills and will develop knowledge on building statistical models and machine learning systems in Julia, with attractive visualizations. This book addresses challenges of real-world data science problems, including: data cleaning, data preparation, inferential statistics, statistical modelling, building high performance machine learning systems, and creating effective visualizations with D3 and Julia.
"synopsis" may belong to another edition of this title.
Anshul Joshi is a Consultant for Data Science in Xebia. He started studying about machine learning and distributed computing during college. He has keen interest in data science, deep learning, and neural networks and has some experience working with Spark and MLlib. Anshul is passionate about his job and is a technology enthusiast and tries to stay up to date with the latest developments.
"About this title" may belong to another edition of this title.
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