Python Programming: Machine Learning with Python, Python for Data Analysis, Python Data Science Handbook - A Crash Course for Learning Python Programming
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Author Description
Discover the world of python with this incredible 3-in-1 book bundle! Do you want to uncover the secrets of python data analysis, data science, and machine learning? Looking for the best ways to familiarize yourself with this amazing language, no matter your level of experience? Then this is the bundle for you! Inside this incredible 3 book collection, you'll discover how you can get started with the world of python. Containing a wealth of practical strategies, tips and tricks, and easy-to-understand explanations, now it's never been easier to begin programming with the world of python. With a breakdown of data science, data analysis, and even the wonders of machine learning, this collection is perfect for anybody looking to begin their programming journey. Inside book one, you'll discover: An Exploration Of Machine Learning Must-Know Terminology, Notations, and Programming Jargon How To Use Conditional Statements How To Work With Pandas, Jupyter and Ipython Tips And Tricks For Creating Machine Learning Algorithms And More! Inside book two, you'll find: An Introduction To The World of Python Python Origins, History, And Function Breaking Down The Basics - Python Fundamentals You Need To Know Understanding Numpy Arrays, Operations, Objects, and The Data Preparing Data, Creating Statistics, and More And Real-Life Examples of Python In Action! And in book three, you'll learn: The Fundamentals of Data Science How Python Can Help You Manage Big Data Essential Strategies For Using Python In Data Science Acquiring, Examining, and Processing Data Exploring The Ethics and Privacy of Big Data And So Much More! So don't wait! It's time for you to discover why python is a favorite language for programmers the world
Menrva's Summary
THE THESIS
This 3-in-1 book bundle aims to demystify Python programming for individuals interested in data analysis, data science, and machine learning, regardless of their prior experience. The collection offers practical strategies, tips, and explanations to facilitate learning Python, covering fundamental concepts and specialized applications. It breaks down key areas such as machine learning algorithms, data manipulation with libraries like Pandas and NumPy, and the core principles of data science, making it suitable for beginners embarking on their programming journey.
THE SCOPE MAP
- An exploration of machine learning terminology, notations, and programming jargon.
- Guidance on using conditional statements and working with tools like Pandas, Jupyter, and Ipython.
- Tips and tricks for creating machine learning algorithms.
- An introduction to Python's origins, history, and fundamental concepts.
- Understanding NumPy arrays, operations, objects, and data preparation.
- Real-life examples of Python in action for data analysis.
- The fundamentals of data science and how Python manages big data.
- Essential strategies for using Python in data science, including data acquisition, examination, and processing.
THE AUTHORITY PERSPECTIVE
This collection appears to offer a comprehensive introduction to Python for data-related fields, targeting a broad audience from beginners to those with some experience. The structure, divided into three distinct books, suggests a progressive learning path covering machine learning, data analysis, and data science fundamentals. The inclusion of practical examples and explanations aims to make complex topics accessible, positioning it as a foundational resource for aspiring programmers and data professionals.
Page Count:
643
Publication Date:
2020-03-16
Publisher:
Independently Published
ISBN-13:
9798626322644
Non-Fiction
Science & Technology
Data Science
Machine Learning
Programming
Python Programming
Computer Science
Community Tags
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