Book Image

The Python Workshop

By : Olivier Pons, Andrew Bird, Dr. Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade
Book Image

The Python Workshop

By: Olivier Pons, Andrew Bird, Dr. Lau Cher Han, Mario Corchero Jiménez, Graham Lee, Corey Wade

Overview of this book

Have you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python.
Table of Contents (13 chapters)

Introduction to Linear Regression

Machine learning is the ability of computers to learn from data. The power of machine learning comes from making future predictions based on the data received. Today, machine learning is used all over the world to predict the weather, stock prices, movie recommendations, profits, errors, clicks, purchases, words to complete a sentence, and many more things.

The unparalleled success of machine learning has led to a paradigm shift in the way businesses make decisions. In the past, businesses made decisions based on who had the most influence. But now, the new idea is to make decisions based on data. Decisions are constantly being made about the future, and machine learning is the best tool at our disposal to convert raw data into actionable decisions.

The first step in building a machine learning algorithm is deciding what you want to predict. When looking at a DataFrame, the idea is to choose one column as the target column or predictor column...