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)

Summary

The reader should now have a good understanding of several machine translation approaches and how neural translation machines are different than their traditional counterparts. We should also now have gained an insight into how to build a neural machine translation system from scratch and how to extend that system in interesting ways. With the information and implementation demonstrations provided, the reader is advised to explore other parallel corpus datasets.

In this chapter, we defined embedding layers but didn't load them with pretrained embeddings, such as GloVe, FastText, and so on. The reader is advised to load the embedding layers with pretrained word vector embeddings and see whether this yields better results. In Chapter 4, Style Transfer in Fashion Industry using GANs, we are going to work through a project related to style transfer in the fashion industry...