Book Image

Intelligent Projects Using Python

By : Santanu Pattanayak
Book Image

Intelligent Projects Using Python

By: Santanu Pattanayak

Overview of this book

This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle.
Table of Contents (12 chapters)

What is a recommender system?

Recommender systems are ubiquitous in today's world. Be it movie recommendations on Netflix or product recommendations on Amazon, recommender systems are making a significant impact. Recommender systems can be broadly classified into content-based filtering systems, collaborative filtering systems, and latent factor-based filtering recommender systems. Content-based filtering relies on hand-coding features for the items based on their content. Based on how the users have rated existing items, a user profile is created and the ranks provided by the user are given to those items:

Figure 6.1: Content-based filtering illustration

As we can see in the preceding diagram (Figure 6.1), User A has bought books named Deep Learning and Neural Networks. Since the content of the book Artificial Intelligence is similar to the two books, the content-based...