What this book covers
Chapter 1, Introduction to Practical Machine Learning Using Python, discusses the main machine learning concepts together with the libraries used by data science professionals to handle the data in Python.
Chapter 2, Machine Learning Techniques – Unsupervised Learning, describes the algorithms used to cluster datasets and to extract the main features from the data.
Chapter 3, Supervised Machine Learning, presents the most relevant supervised algorithms to predict the labels of a dataset.
Chapter 4, Web Mining Techniques, discusses the main techniques to organize, analyze, and extract information from web data
Chapter 5, Recommendation Systems, covers the most popular recommendation systems used in a commercial environment to date in detail.
Chapter 6, Getting Started with Django, introduces the main Django features and characteristics to develop a web application.
Chapter 7, Movie Recommendation System Web Application, describes an example to put in practice the machine learning concepts developed in Chapter 5, Recommendation Systems and Chapter 6, Getting Started with Django, recommending movies to final web users.
Chapter 8, Sentiment Analyser Application on Movie Reviews, covers another example to use the knowledge explained in Chapter 3, Supervised Machine Learning, Chapter 4, Web Mining Techniques, and Chapter 6, Getting Started with Django, analyzing the sentiment of the movies' reviews online and their importance.
