Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python PDF AZW3 EPUB MOBI TXT Download

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you’ll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that “learn” from dataUnsupervised learning methods for extracting meaning from unlabeled data.

Peter Gedeck
O'Reilly Media; 2nd edition (June 2, 2020)
368 pages
English
978-1492072942

File Size: 16 MB
Available File Formats: PDF AZW3 DOCX EPUB MOBI TXT or Kindle audiobook Audio CD(Several files can be converted to each other)
Language: English, Francais, Italiano, Espanol, Deutsch, chinese

Peter Bruce is the Founder and Chief Academic Officer of the Institute for Statistics Education at Statistics.com, which offers about 80 courses in statistics and analytics, roughly half of which are aimed at data scientists. He has authored or co-authored several books in statistics and analytics, and he earned his Bachelor’s degree at Princeton, and Masters degrees at Harvard and the University of Maryland.^Andrew Bruce, Principal Research Scientist at Amazon, has over 30 years of experience in statistics and data science in academia, government and business. The co-author of Applied Wavelet Analysis with S-PLUS, he earned his bachelor’s degree at Princeton, and PhD in statistics at the University of Washington^Peter Gedeck, Senior Data Scientist at Collaborative Drug Discovery, specializes in the development of machine learning algorithms to predict biological and physicochemical properties of drug candidates. Co-author of Data Mining for Business Analytics, he earned PhD’s in Chemistry from the University of Erlangen-Nürnberg in Germany and Mathematics from Fernuniversität Hagen, Germany. <div id="

The content of this book gets 5 stars. I especially appreciate the author including Python this time around. However, O’Reilly decided to print this book in black and white. That isn’t acceptable for a $50+ book where you need to be able to distinguish between colored lines on charts.Thankfully I have an O’Reilly subscription where I can view the digital book in color, as I imagine the author intended.

I read through a previous version of this book when I was mainly using R, and it was incredible. One of the better stats application books I’ve read. Since I switched to Python this year, I was very happy to see that they released a version with Python content. However, I’ve thus far been very disappointed. The stats content is still great, but overall, the Python code is very often missing comments, doesn’t run properly, or some mix of both. The book is still a good primer on the stats that a data scientist needs, but don’t expect the code snippets to provide much guidance.

The book is well thought out and the explanations of the concepts are sound. The subtitle is a little misleading giving the impression that the book covers both R and Python equally. The reality is that is puts much more emphasis on R programming language and the Python code is an after thought.

Examples use data that is not providedHard to followCode is provided with little or no explanationWithout the underlying data you can’t reproduce itNot very enlightening

This was supposed to be a new book. Seller should have caught this. On page 114-115 it looks like the publishing page cutter got crimped or something so that the book pages were as seen on the photos. Don’t have time to send back and get another one. Disappointment.

I had purchased a new physical copy of the book, and realized there were several pages that were blank and missing. I contacted O’Reilly about the problem and they were extremely quick with a resolution! They were able to give me a different copy so I could read it without the missing pages. The content of the book itself is good, except in all black and white, which doesn’t bother me personally but may bother someone else when it comes to the graphs. I think the R and Python content are both great, and it keeps the code concise and quick to the point. Great for R beginners, but for python users I would recommend a little more experience. As for the math parts, its great for those who are new to statistics and gives easy to read explanations, and a great refresher for those who just want to review some of the concepts. I especially like the sections provided for further reading, which have been helpful.

Glad to get the python scripts for the content. I was expecting a color print pages but this is black and white.

The book is amazing and very useful, for beginners also. The most valuable from my point of view is presence of code both for R and Python, which helps understand the syntax better for one language if you know another.

Content is extremely well written, you’ll learn the fundamentals of data science and gain an understanding of how data can be used to model different situations, as well as the mathematical/practical methods to do so.

I got this because I am taking a data analytics course that is not explained that well and I need to fill up my gaps in statistics. It is a good book

It’s a good skim through read rather than an in depth book. I I appreciate it being a good beginner friendly book.

The book provides good explanations of complicated issues

At this huge price was expecting color print but got greyscale edition this disappointed me.Book content is awesome but color print was expected.😢😢

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File Size: 16 MB

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