By Samir Madhavan
ISBN-10: 1784390151
ISBN-13: 9781784390150
Approximately This Book
Master info technological know-how tools utilizing Python and its libraries
Create facts visualizations and mine for patterns
Advanced ideas for the 4 basics of information technology with Python - information mining, info research, info visualization, and desktop learning
Who This e-book Is For
If you're a Python developer who desires to grasp the realm of information technology then this ebook is for you. a few wisdom of knowledge technological know-how is assumed.
What you are going to Learn
Manage information and practice linear algebra in Python
Derive inferences from the research by way of acting inferential statistics
Solve info technology difficulties in Python
Create high-end visualizations utilizing Python
Evaluate and practice the linear regression strategy to estimate the relationships between variables.
Build advice engines with a number of the collaborative filtering algorithms
Apply the ensemble the way to increase your predictions
Work with gigantic info applied sciences to address information at scale
In Detail
Data technology is a comparatively new wisdom area that's utilized by a variety of agencies to make info pushed judgements. facts scientists need to put on a variety of hats to paintings with information and to derive price from it. The Python programming language, past having conquered the medical neighborhood within the final decade, is now an integral instrument for the information technology practitioner and a must-know device for each aspiring info scientist. utilizing Python will provide you with a quick, trustworthy, cross-platform, and mature atmosphere for information research, desktop studying, and algorithmic challenge solving.
This accomplished consultant is helping you progress past the hype and go beyond the speculation through giving you a hands-on, complex examine of information science.
Beginning with the necessities of Python in facts technology, you'll learn how to deal with info and practice linear algebra in Python. you are going to circulation directly to deriving inferences from the research by way of appearing inferential records, and mining info to bare hidden styles and traits. you'll use the matplot library to create high-end visualizations in Python and discover the basics of desktop studying. subsequent, you'll follow the linear regression method and likewise learn how to follow the logistic regression strategy to your purposes, earlier than developing advice engines with quite a few collaborative filtering algorithms and bettering your predictions by way of utilising the ensemble methods.
Finally, you are going to practice K-means clustering, in addition to an research of unstructured facts with diverse textual content mining concepts and leveraging the facility of Python in huge information analytics.
Style and approach
This e-book is an easy-to-follow, accomplished consultant on information technological know-how utilizing Python. the themes lined within the booklet can all be utilized in actual international scenarios.
Read or Download Mastering Python for Data Science PDF
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Extra info for Mastering Python for Data Science
Example text
Seed function. If you call it twice with the same value, it will cause the random module to reproduce the same sequence of numbers. Listing 2-9 demonstrates how the seed function can be used to create predictable sequences. Listing 2-9. info Chapter 2 ■ Exploring Python If you run this small script, you will see the same sequence of numbers, repeated twice. Have a look at Table 2-7 for a few of the capabilities of the random module. Table 2-7. Some Functions in the random Module Function Description seed Seeds the random number generator randint Returns a random integer between two values choice Selects a random element from a collection random Return a float between 0 and 1 Summary We’ve seen that you can use boolean logic to make decisions in Python code.
The default is 32-bit, but you may have grabbed a 64-bit installation. To find out what you have, open IDLE, and read the very top bit of text. 1600 32 bit (Intel)] on win32 Type "copyright", "credits" or "license()" for more information. Notice where it says 32 bit (Intel); this means I am using a 32 bit version of Python. This means all my modules must be 32 bit modules. If you are using a 64 bit version of Python, all your modules must be 64 bit (despite what you might expect). It is possible, however, to be running a 32 bit version of Python on a 64 bit version of Windows.
Let’s see an example: my_tank = Tank("Bob") This creates a new tank called Bob and calls __init__ to initialize it. Bob the tank is then assigned to the variable my_tank, which is called an instance of the Tank class. We can now treat my_tank as an individual object—passing it into functions, storing it in lists, and so forth, or we can access the properties individually. name would display Bob. info Chapter 2 ■ Exploring Python Adding to our Class With just one method, the Tank class can’t do anything interesting.