Python for Data Science: A Crash Course for Data Science and Analysis, Python Machine Learning and Big Data

COMPUTER SCIENCE ACADEMY

ISBN 10: 1801255253 / ISBN 13: 9781801255257

Edité par GIALE LTD, 2020

A propos de cet article

178 pages. 9.02x5.98x0.38 inches. In Stock.

N° de réf. du vendeur zk1801255253

Détails bibliographiques

• Titre: Python for Data Science: A Crash Course for Data Science and Analysis, Python Machine Learning and Big Data
• Éditeur: GIALE LTD
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 1801255253
• ISBN à 13 chiffres: 9781801255257
• Reliure: Paperback
• État de l'article: Brand New

A propos de ce titre

Synopsis

Are you looking to master the fundamental concepts of Data Science?


Do you want to learn the Python programming language?


Do you want to develop a solid understanding of all the latest innovative technologies?
 
This is the book for you!
 
This book is essential to help you master the core concepts of Python programming and utilize your coding skills to yze a large volume of data.
 
 
This programming language can be used for a variety of coding projects including machine learning algorithms, web applications, data mining and ualization, game development.
 
Some of the highlights of this book include:
 
The five major stages of the TDSP lifecycle
Installation instructions for Python
Python coding concepts such as data types, classes, and objects variables, numbers, constructor functions, Booleans and much more.
Learn the functioning of various data science libraries like Scikit-Learn, which has evolved as the gold standard for machine learning and data ysis.
Deep dive into the Matplotlib library, which offers ualization tools and science computing modules supported by SciPy and learn how to create various graphs using Matplotlib and Pandas library. 
Learn how machine learning allows ysis of large volumes of data and delivers faster and more accurate results.
Overw of four different machine learning algorithms.
Learn how companies are able to employ a predictive ytics model to gain an understanding of customer interactions with their products or services based on customer's feelings or emotions shared on the social media platforms. 
 
Every concept in this book is explained with examples and exercises so you can learn and test your learning at the same time.