Python Data Science: from Beginner to Experts About Techniques of Data Mining, Big Data Analytics and Science, Python Programming and How to Use Them in Business - Tapa blanda

Sinopsis

Have you ever been thought what it would be like if you dared to expand your python programming skills to include data science? Or are you looking for a new job in the technological and scientific world? Then keep reading because I have what you need!

Working with machine learning is something that a lot of different companies want to focus on now. 

They like the idea of being able to get a system to learn while they are not there. They like to provide a better kind of customer service than they could have before. And they like all of the opportunities that are going to present themselves when it comes to this kind of programming. And when they can provide it all and learn how to do all the different parts with the help of Python, that can just make that much easier.  

This guidebook has explored a lot of the different topics that can come up with this. 

The purpose of the book is to help you to understand how to work with Python, what is all available with Python, and so much more. 

Some of the different topics we will discuss in this guidebook to help you to get started with coding in Python Data Science will include:

• Techniques of Algorithmic programming
• The Database Access with Python
• What Can I Do with GUI Programming?
• Recent Advancements in Data Analysis
• Python Data Structures
• Numba - Just in Time Python compiler
• Comparing Pipeline Data Models: Is PODS Spatial the Right Solution?
• Visualization and Results
• Most Common Data Science Problems:
• Linear Classifiers
• Setting Up PyCharm
• Data frames
• Why Python for Big Data?

Are you wondering if that your PC can be an algorithms machine? 

Even if you have never heard that it’s possibile, this book will deny it to you.

If you want to know how, scroll up and click the buy now button to get your copy.

"Sinopsis" puede pertenecer a otra edición de este libro.