Supervised Machine Learning with Python
Develop rich Python coding practices while exploring supervised machine learning
About the Book
Teach your machine to think for itself!
- Delve into supervised learning and grasp how a machine learns from data
- Implement popular machine learning algorithms from scratch, developing a deep understanding along the way
- Explore some of the most popular scientific and mathematical libraries in the Python language
Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood.
This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning.
By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems.
What you will learn
- Crack how a machine learns a concept and generalize its understanding to new data
- Uncover the fundamental differences between parametric and non-parametric models
- Implement and grok several well-known supervised learning algorithms from scratch
- Work with models in domains such as ecommerce and marketing
- Expand your expertise and use various algorithms such as regression, decision trees, and clustering
- Build your own models capable of making predictions
- Delve into the most popular approaches in deep learning such as transfer learning and neural networks
Who this book is for
This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals.
Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools.
As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
Our students work
with the Best
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video CoursesSubscribe now
Master prominent technologies at full length and become a valued certified professional.Explore Now