Coding with Python: Python for Data Analysis and Machine Learning, Let's Make Data Talk, (Paperback)

Nowadays, analysts must manage data characterized by extraordinary variety, velocity, and volume.

Using Machine Learning and Data visualization, you can automate and perform virtually any data analysis task, no matter how large or complex the data is . So it become necessary to learn how to visualize data in order to make decision. This book come to fulfill this needs and give you the necessary tools to become more comfortable with Data Analysis.

Why This Book ?

• A Detailed explanation of main topics: It can be to frustrating to understand to difference between terms in Data science so this book assist you all the way to put you in the right path of learning . From the basics to the most complex used topics in data Analysis .
• Data science Process: A complete explanation of Data science steps from scratch and the programming languages used like R, Ruby, python and its librairies . In addition, this book provides you an image processing in depth by giving you the images classification patterns using Django .
• Hands on Practical Exercices: In order to gives you a jumstart to data analysis, This book give you exercices in handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes.

What you will learn in this book

• PYTHON for Data Analysis and Machine Learning
• Chapter 1: Machine learning
• Chapter 2: Data Science
• Chapter 3: Data Science Training, Data Science - Machine Learning with Python
• Chapter 4: Computer programming for beginners
• Chapter 5: Why programing ?
• Chapter 6: How to learn your first language programming
• Chapter 7: How beneficial is Django to existing Python developers
• Chapter 8: Why is Python a favourite start up language?
• Chapter 9: The role of Python in image applications
• Chapter 10: Development of the Python and its distinctive features
• PRACTICAL EXERCISES