||7 of 8 people found the following review helpful.| Julia for Data Science - Not with this Book!|By Customer|As is the case with many Packt publications this work is a genuinely amateurish effort! By way of example, consider pages 23 through 26:
1) Two examples of Julia code are misplaced: a) Page 23 - "pmap refers to parallel map. For example:" the Julia code which follows uses @parallel, not pmap. The ex|About the Author||Anshul Joshi|Anshul Joshi is a data scientist with experience in recommendation systems, predictive modeling, neural networks, and high performance computing. His research interests are deep learning, artificial intelligence, computatio
Key Features
An in-depth exploration of Julia's growing ecosystem of packages
Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization
Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data sets
Book Description
Julia is a fast and high performing language that's perfectly suited to data science with a mature package...
[PDF.iq68] Julia for Data Science Rating: 4.58 (470 Votes)
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