Get Data Science from Scratch: First Principles with Python PDF

By Joel Grus

ISBN-10: 1491904402

ISBN-13: 9781491904404

Facts technology libraries, frameworks, modules, and toolkits are nice for doing information technology, yet they're additionally so as to dive into the self-discipline with no really realizing facts technology. during this ebook, you'll find out how some of the so much primary information technological know-how instruments and algorithms paintings by means of enforcing them from scratch.

If you've got an inherent ability for arithmetic and a few programming talents, writer Joel Grus may help you get pleased with the maths and data on the middle of information technological know-how, and with hacking talents you must start as an information scientist. Today's messy glut of information holds solutions to questions no one's even inspiration to invite. This publication offers you the knowledge to dig these solutions out.
•Get a crash path in Python
•Learn the fundamentals of linear algebra, data, and probability—and know the way and while they're utilized in facts science
•Collect, discover, fresh, munge, and control data
•Dive into the basics of laptop learning
•Implement types similar to k-nearest buddies, Naive Bayes, linear and logistic regression, selection bushes, neural networks, and clustering
•Explore recommender structures, normal language processing, community research, MapReduce, and databases

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Although it is very easy to create visualizations, it’s much harder to produce good ones. There are two primary uses for data visualization: • To explore data • To communicate data In this chapter, we will concentrate on building the skills that you’ll need to start exploring your own data and to produce the visualizations we’ll be using throughout the rest of the book. Like most of our chapter topics, data visualization is a rich field of study that deserves its own book. Nonetheless, we’ll try to give you a sense of what makes for a good visualization and what doesn’t.

I) Here re is the module containing functions and constants for working with regular expressions. After this type of import you can only access those functions by prefix‐ ing them with re.. I) You might also do this if your module has an unwieldy name or if you’re going to be typing it a lot. match>" However, since you are not a bad person, you won’t ever do this. 7 uses integer division by default, so that 5 / 2 equals 2. 5. Every code example in this book uses this new-style division. In the handful of cases where we need integer division, we can get it with a double slash: 5 // 2.

Rather than attempt a compre‐ hensive treatment of these options, we’ll just use (and call attention to) some of them in our examples. 38 | Chapter 3: Visualizing Data Although we won’t be using much of this functionality, matplotlib is capable of producing complicated plots within plots, sophistica‐ ted formatting, and interactive visualizations. Check out its docu‐ mentation if you want to go deeper than we do in this book. Bar Charts A bar chart is a good choice when you want to show how some quantity varies among some discrete set of items.

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Data Science from Scratch: First Principles with Python by Joel Grus

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