Python Data Science

The Ultimate Handbook for Beginners on How to Explore NumPy for Numerical Data, Pandas for Data Analysis, IPython, Scikit-Learn and Tensorflow for Machine Learning and Business
Narrated by: Clay Willison
Length: 3 hrs and 21 mins
5 out of 5 stars (63 ratings)

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Publisher's Summary

If you’re tired of licensing third-party software for data analysis, Python Data Science will help you do it for yourself!

Recently, more and more companies are learning that they need to make data-driven decisions. And with big data and data science on the rise, we now have more data than we know what to do with.

In fact, without a doubt, you have already experienced data science in one way or another. Obviously, you are interacting with data science products every time you search for information on the web by using search engines such as Google, or asking for directions with your mobile phone.

Data science is the science and technology focused on collecting raw data and processing it in an effective manner. It is the combination of concepts and methods that make it possible to give meaning and understand ability to huge volumes of data.

Data science has been the force behind resolving some of our most common daily tasks for several years. In nearly all of our daily work, we directly or indirectly work on storing and exchanging data. With the rapid development of technology, the need to store data effectively is also increasing. That's why it needs to be handled properly. Basically, data science unearths the hidden insights of raw-data and uses them for productive output.

Python is often used in data science today because it is a mature programming language that has excellent properties for newbie programmers. Some of the most remarkable of these properties are its easy to read code, suppression of non-mandatory delimiters, dynamic typing, and dynamic memory usage. Python is an interpreted language, and it can be executed in the Python console without any need to compile to machine language.

Python Data Science teaches a complete course of data science, including key topics like data integration, data mining, python etc. We will explore NumPy for numerical data, Pandas for data analysis, IPython, Scikit-learn and Tensorflow for machine learning and business.

Each of the sections in this audiobook is devoted to one of the most interesting aspects of data analysis and processing. The following are some of the major topics covered in Python Data Science:

  • Understanding Data Science
  • Getting Started with Python for Data Scientists
  • Descriptive statistics
  • Data Analysis and Libraries
  • NumPy Arrays and Vectorized Computation
  • Data Analysis with Pandas
  • Data Visualization
  • Data Mining
  • Classifying with Scikit-learn Estimators
  • Giving Computers the Ability to Learn from Data
  • Training Machine Learning Algorithms

The Python ecosystem for data science discussed within Python Data Science includes SciPy, NumPy, Matplotlib, Pandas, and Scikit-learn, which provides all of the data science algorithms.

Data processing and analysis is one of the hottest areas of IT, where developers who can handle projects of any level, from social networks to trained systems, are constantly required. We hope this audiobook will be the starting point for your journey into the fascinating world of data science.

To get started on your Python adventure, just get this audiobook now.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2019 Steve Blair (P)2019 Steve Blair

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Best book for python data analysis


This is an excellent reference book for people working with data science. Remember, 80% of the effort in machine learning, data analysis or data science in general is about processing data and understanding data. This book is for that purpose and I think it's the best book out there about data processing, analysis and visualization using python. If you look for hardcore machine learning, go for other books. Highly recommended!

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Nice book!!


For the Introduction to Machine learning, I took this course and this is quite helpful. Recommend you check this out in case you want to learn practical examples.

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Best Python book for a beginner


This is the most informative book on python that I have ever purchased. You will be astonished how muсh you can dо in this dialect оnсе уоu knоw the rudiments. This book is exceptionally elegantly composed by the writer and I very prescribe this book to every one of you folks.

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Thanks to creator.


I am currently taking a Machine Learning course from Udacity and this book has proven to be a great reference guide for several projects and quizes. Although it does not go in depth in regards to machine learning (although almost half of the book is dedicated to it), it does give an understanding of essential concepts.

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Nice book.


I like this book. This book helped explain everything and even had the output of the code to show what each code block would do. I ended up searching around on the author's website and he does have all of the source code in a zip file. Easy book to help you start understanding Data Science.

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Great guidebook


That was a very informative book. This book all of the information very easy to read. This book I will learn Python Data Science very effectively. The author well explanation and step by step guide very useful for Python Data Science programming. I appreciate this book. Thanks to the author

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Introductory Text


I love this book as a reference. Clear, efficient but detailed explanations. It is not designed as a textbook but as a reference. When I wonder "what is that test used for again?" this is the first thing I reach for. Sure, Google has become universal for that too, but I like having a single hard copy reference that I can get to know and that becomes a trustworthy old friend. This book is taking on that role for me.

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Great book for Python Data Science

Python Data Science that's a very resourceful book. This book all of the information very easy to listen. It is an extraordinary prologue to the fundamental ideas of python coding and has been helpful in getting every one of the understudies to a point where we can start to do a few material sciences utilizing in only a week or two. The author very clearly wrote this book. This book helps me developing my skill. Thanks to the author

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That was a very informative book


The copious notes scattered throughout this book are pure gold, mined from the obvious experiences of the authors while working in the field. If there ever is a Machine Learning equivalent to the venerable Engineering Notebook" for electronics, I feel these two authors could write it.

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Good material, not so good performance

The material is good for someone new to data science but the performance is not so good specially when reading code.
The accompanied PDF is not consistent with the narrative.
The book is using Python 2 which is outdated.

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  • Jordan
  • 10-19-19

Recommended

I think it is a territory that is regularly ignored by specialized course book, yet should be underscored to peruses who may some time or another become an information professional. Generally speaking, it's an awesome book and worths your push to dig into.

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  • Noah
  • 10-19-19

Useful Book


This guidebook is going to take some time to talk about machine learning and what it is all about. There are a lot of different parts that come with machining, and we are going to start this guidebook taking a look at the basics of data science, machine learning, and artificial intelligence and more at the beginning of this guidebook.

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  • Jessica
  • 10-19-19

Awesome book


The best book I've found so far at explaining the theory of Data Science. If you are looking to get into data science and don't want to just start plugging away with Python or R then this is a great starter book that will teach you the lingo and the concepts that surround data science.

10 people found this helpful

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  • Finn
  • 10-19-19

nformative


This is an interesting book on data science. In have found good information that I haven't found on other books before. Excellent.

10 people found this helpful

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  • Carlos
  • 10-19-19

Perfect for beginners.


I feel bad as I had to return the book. I just finished this book. I am trying to get into Data Science for Beginners. I guess even practising machine learning. For me it would have been better if the examples were more focused Programming Code.

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  • Olivia
  • 10-19-19

Amazing


This book is utilitarian and supportive.This book is an incredible instructional booklet for anybody doing specialized programming interviews, regardless of whether information science isn't the peruser's forte. The writer gives phenomenal inquiries that are applicable to pretty much all programming interviews

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  • David
  • 10-19-19

Perfect Guide


Well-written and easy-to-understand, this book gives a new-comer like me a conceptual framework to think about problems in data science. It helps me to understand what the field really is and what the workflow of a data science project looks like.

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  • Mason R Simmons
  • 10-20-19

Really like this

I really like this book. It covers a lot of ground without being a lot of pages. Also, they remember to mention the practical things, e.g. some differences in terminology across statistics vs. data mining fields. Excellent review book, for example.

9 people found this helpful

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  • Kai A Hicks
  • 10-20-19

Good Surveyor Book


Reads super easily, and doesn't dumb it down to the point that I don't feel like I'm not getting anything

8 people found this helpful

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  • Alicia R How
  • 10-20-19

Good book.


The book explains all the topics in good detail and also details the implementation in R or Python. But, I suggest that People who has basic knowledge of statistics to buy this book or few concepts might be confusing.

5 people found this helpful