Book Image

Data Science Algorithms in a Week - Second Edition

By : David Natingga
Book Image

Data Science Algorithms in a Week - Second Edition

By: David Natingga

Overview of this book

Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical analysis, these models can be leveraged to gain new knowledge from existing data as well. Data Science Algorithms in a Week addresses all problems related to accurate and efficient data classification and prediction. Over the course of seven days, you will be introduced to seven algorithms, along with exercises that will help you understand different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets. This book also guides you in predicting data based on existing trends in your dataset. This book covers algorithms such as k-nearest neighbors, Naive Bayes, decision trees, random forest, k-means, regression, and time-series analysis. By the end of this book, you will understand how to choose machine learning algorithms for clustering, classification, and regression and know which is best suited for your problem
Table of Contents (16 chapters)
Title Page
Packt Upsell
Contributors
Preface
Glossary of Algorithms and Methods in Data Science
Index

Introduction


Python is a general-purpose programming and scripting language. Its simplicity and extensive libraries make it possible to develop an application that is compatible with the modern requirements of technology quickly.

Python code is written in files with the suffix .py, and can be executed with the python command.

Python Hello World example

The simplest program in Python prints a single line of text.

Input:

source_code/appendix_c_python/example00_helloworld.py
print "Hello World!"

Output:

$ python example00_helloworld.py
Hello World!

Comments

Comments are not executed in Python. They start with the # character, and end with the end of the line.

Input:

# source_code/appendix_c_python/example01_comments.py
print "This text will be printed because the print statement is executed."
#This is just a comment and will not be executed.
#print "Even commented statements are not executed."
print "But the comment finished with the end of the line."
print "So the 4th and 5th line of the code are executed again."

Output:

$ python example01_comments.py 
This text will be printed because the print statement is executed
But the comment finished with the end of the line.
So the 4th and 5th line of the code are executed again.