Python Machine Learning
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More About This Title Python Machine Learning


Python makes machine learning easy for beginners and experienced developers

With computing power increasing exponentially and costs decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. However, machine learning is not for the faint of heart—it requires a good foundation in statistics, as well as programming knowledge. Python Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. 

Readers will get started by following fundamental topics such as an introduction to Machine Learning and Data Science. For each learning algorithm, readers will use a real-life scenario to show how Python is used to solve the problem at hand.

•          Python data science—manipulating data and data visualization

•          Data cleansing

•          Understanding Machine learning algorithms
•          Supervised learning algorithms

•          Unsupervised learning algorithms

•          Deploying machine learning models 

Python Machine Learning is essential reading for students, developers, or anyone with a keen interest in taking their coding skills to the next level. 


Wei-Meng Lee is a technologist and founder of Developer Learning Solutions (, a technology company specializing in hands-on training on the latest mobile technologies. Wei-Meng has many years of training experiences and his training courses place special emphasis on the learning-by-doing approach. His hands-on approach to learning programming makes understanding the subject much easier than reading books, tutorials, and documentations. His name regularly appears in online and print publications such as,, and CoDe Magazine.


Chapter 1 - What is Machine Learning? 
Chapter 2 - Extending Python using Numpy 
Chapter 3 - Manipulating Tabular Data using Pandas
Chapter 4 - Data Visualization using matplotlib 
Chapter 5 - Getting started with Scikit-Learn
Chapter 6 - Regression Algorithms 
Chapter 7 - Classification Algorithms 
Chapter 8 - Clustering Algorithms 
Chapter 9 - Anomaly Detection Algotithms 
Chapter 10 - Deploying your learning model as a web service using Python