Python Programming: 3 Menuscripts Crash Course Coding With Python Data Science

Python Programming: 3 Menuscripts Crash Course Coding With Python Data Science
ePUB

Book Description
This book is the perfect guide for people who want to learn about Phyton programming, in particular its application for data science.
There are so many great ways that you can use the data you have been collecting for some time now, and being able to complete the process of data visualization will ensure that you get it all done, when you are ready to get started with Python data science.
This guide book contains:
  • What Is Data Science And Why Should You Learn It Using Python
  • Can I Use Probability And Statistics To Help Me With Machine Learning?
  • Work With Numpy
  • Work With Pandas
  • Learning About Functions
  • Identifying The Nearest Neighbors
  • Learning About Functions
  • Deep Learning Vs Machine Learning
  • Applications Of Big Data Analysis
And many more!
Loops are going to be next on the list of topics we need to explore when we are working with Python. These are going to be a great way to clean up some of the code that you are working on so that you can add in a ton of information and processing in the code, without having to go through the process of writing out all those lines of code. For example, if you would like a program that would count out all of the numbers that go from one to one hundred, you would not want to write out that many lines of code along the way. Or if you would like to create a program for doing a multiplication table, this would take forever as well. But doing a loop can help to get all of this done in just a few lines of code, saving you a lot of time and code writing in the process.  

Content

PYTHON CRASH COURSE
Chapter 1 - What Is Python and Why Should You Learn It
Chapter 2 - Variables and Operators
Chapter 3 - Learn About Simple Data Types
Chapter 4 - Conditional Statements in Python and Control Flow Statements
Chapter 5 - Working With Functions
Chapter 6 - Object-Oriented Programming
Chapter 7 - Working with Files
Chapter 8 - Python From Scratch
Chapter 9 – How Coding Works
Chapter 10 - Python Libraries
Chapter 11 – Getting Program Functioning to Work

CODING WITH PYTHON
Chapter 1 Phython Programming Basics
Chapter 2 - What Is Scikit-Learn, and Why Should I Learn About It?
Chapter 3 - Essential Libraries And Tools In Python
Chapter 4 – Learn Modules
Chapter 5 - Machine Learning Datasets
Chapter 6 - Training Simple Machine Learning Algorithms for Classification
Chapter 7 - Unsupervised Machine Learning
Chapter 8 - Learning in Artificial Neural Networks
Chapter 9 - The Perceptron
Chapter 10 - Execution and Repetitive Tasks
Chapter 11 - Variables and Strings

PYTHON DATA SCIENCE
Chapter 1 - What Is Data Science And Why Should You Learn It Using Python
Chapter 2 – Statistics and Probability
Chapter 3 - Work With Numpy
Chapter 4 – Work With Pandas
Chapter 5 - Learning About Functions
Chapter 6 - Developing a Machine Learning Model with Python
Chapter 7 - Identifying the Nearest Neighbors
Chapter 8 - Deep Learning vs Machine Learning
Chapter 9 - Other Basics of the Python Code
Chapter 10 - Modules
Chapter 11 - Applications of Big Data Analysis

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