Link to the GitHub Repository containing the code examples and additional
material: [https://github.com/rasbt/python-machi...](https://github.com/rasbt
/python-machine-learning-book)
Many of the most innovative breakthroughs and exciting new technologies can be
attributed to applications of machine learning. We are living in an age where
data comes in abundance, and thanks to the self-learning algorithms from the
field of machine learning, we can turn this data into knowledge. Automated
speech recognition on our smart phones, web search engines, e-mail spam
filters, the recommendation systems of our favorite movie streaming services –
machine learning makes it all possible.
Thanks to the many powerful open-source libraries that have been developed in
recent years, machine learning is now right at our fingertips. Python provides
the perfect environment to build machine learning systems productively.
This book will teach you the fundamentals of machine learning and how to
utilize these in real-world applications using Python. Step-by-step, you will
expand your skill set with the best practices for transforming raw data into
useful information, developing learning algorithms efficiently, and evaluating
results.
You will discover the different problem categories that machine learning can
solve and explore how to classify objects, predict continuous outcomes with
regression analysis, and find hidden structures in data via clustering. You
will build your own machine learning system for sentiment analysis and
finally, learn how to embed your model into a web app to share with the world

2024-09-11