Book Image

Data Science with Python

By : Rohan Chopra, Aaron England, Mohamed Noordeen Alaudeen
Book Image

Data Science with Python

By: Rohan Chopra, Aaron England, Mohamed Noordeen Alaudeen

Overview of this book

Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. You will learn three major techniques in machine learning: unsupervised learning, supervised learning, and reinforcement learning. You will also explore basic classification and regression techniques, such as support vector machines, decision trees, and logistic regression. As you make your way through the book, you will understand the basic functions, data structures, and syntax of the Python language that are used to handle large datasets with ease. You will learn about NumPy and pandas libraries for matrix calculations and data manipulation, discover how to use Matplotlib to create highly customizable visualizations, and apply the boosting algorithm XGBoost to make predictions. In the concluding chapters, you will explore convolutional neural networks (CNNs), deep learning algorithms used to predict what is in an image. You will also understand how to feed human sentences to a neural network, make the model process contextual information, and create human language processing systems to predict the outcome. By the end of this book, you will be able to understand and implement any new data science algorithm and have the confidence to experiment with tools or libraries other than those covered in the book.
Table of Contents (10 chapters)


We live in a world where we are constantly surrounded by data. As such, being able to understand and process data is an absolute necessity.

Data Science is a field that deals with the description, analysis, and prediction of data. Consider an example from our daily lives: every day, we utilize multiple social media applications on our phones. These applications gather and process data in order to create a more personalized experience for each user – for example, showing us news articles that we may be interested in, or tailoring search results according to our location. This branch of data science is known as machine learning.

Machine learning is the methodical learning of procedures and statistical representations that computers use to accomplish tasks without human intervention. In other words, it is the process of teaching a computer to perform tasks by itself without explicit instructions, relying only on patterns and inferences. Some common uses of machine learning algorithms are in email filtering, computer vision, and computational linguistics.

This book will focus on machine learning and other aspects of data science using Python. Python is a popular language for data science, as it is versatile and relatively easy to use. It also has several ready-made libraries that are well equipped for processing data.