By Anshul Joshi
- An in-depth exploration of Julia's starting to be surroundings of packages
- Work with the main strong open-source libraries for deep studying, facts wrangling, and information visualization
- Learn approximately deep studying utilizing Mocha.jl and provides velocity and excessive functionality to facts research on huge information sets
Julia is a quick and excessive acting language that is ideally suited to information technological know-how with a mature package deal atmosphere and is now function entire. it's a reliable instrument for a knowledge technological know-how practitioner. there has been a well-known publish at Harvard company assessment that facts Scientist is the sexiest task of the twenty first century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century).
This ebook can assist you get familiarised with Julia's wealthy surroundings, that's continually evolving, permitting you to stick on best of your game.
This publication comprises the necessities of knowledge technology and provides a high-level evaluation of complex records and strategies. you are going to dive in and should paintings on producing insights by means of appearing inferential statistics, and should demonstrate hidden styles and tendencies utilizing information mining. This has the sensible assurance of facts and laptop studying. you are going to increase wisdom to construct statistical types and computing device studying platforms in Julia with beautiful visualizations.
You will then delve into the realm of Deep studying in Julia and may comprehend the framework, Mocha.jl with that you can create synthetic neural networks and enforce deep learning.
This booklet addresses the demanding situations of real-world facts technology difficulties, together with facts cleansing, info training, inferential records, statistical modeling, development high-performance laptop studying structures and developing powerful visualizations utilizing Julia.
What you are going to learn
- Apply statistical types in Julia for data-driven decisions
- Understanding the method of information munging and information guidance utilizing Julia
- Explore suggestions to imagine information utilizing Julia and D3 dependent packages
- Using Julia to create self-learning platforms utilizing leading edge computing device studying algorithms
- Create supervised and unsupervised computer studying platforms utilizing Julia. additionally, discover ensemble models
- Build a suggestion engine in Julia
- Dive into Julia's deep studying framework and construct a method utilizing Mocha.jl
About the Author
Anshul Joshi is an information scientist with event in advice structures, predictive modeling, neural networks, and excessive functionality computing. His study pursuits are deep studying, synthetic intelligence, computational physics, and biology.
Most of the time, he should be stuck exploring GitHub or making an attempt whatever new which he can get his fingers on. He blogs on https://anshuljoshi.com/.
Table of Contents
- The basis – Julia's Environment
- Data Munging
- Data Exploration
- Deep Dive into Inferential Statistics
- Making feel of information utilizing Visualization
- Supervised computing device Learning
- Unsupervised computing device Learning
- Creating Ensemble Models
- Time Series
- Collaborative Filtering and advice System
- Introduction to Deep Learning
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Extra info for Julia for Data Science
Julia for Data Science by Anshul Joshi