We will now look at implementing an autonomous self-driving racing car that learns to drive by itself on a racing track using deep Q networks. The driver and the car will act as the agent, while the racing track and its surroundings act as the environment. We will be using an OpenAI Gym CarRacing-v0 framework as the environment. The states and the rewards are going to be presented to the agent by the environment, while the agent will act upon those by taking appropriate actions. The states are in the form of images taken from a camera in front of the car. The actions that the environment accepts are in the form of the three-dimensional vector a ∈ R3 where the first component is used for turning left, the second component is used for moving forward and the third component is used for moving right. The agent will interact with the...
Intelligent Projects Using Python
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Intelligent Projects Using Python
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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.
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Current Title:
Intelligent Projects Using Python
Table of Contents (12 chapters)
Preface
Free Chapter
Foundations of Artificial Intelligence Based Systems
Transfer Learning
Neural Machine Translation
Style Transfer in Fashion Industry using GANs
Video Captioning Application
The Intelligent Recommender System
Mobile App for Movie Review Sentiment Analysis
Conversational AI Chatbots for Customer Service
Autonomous Self-Driving Car Through Reinforcement Learning
CAPTCHA from a Deep-Learning Perspective
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Customer Reviews