Machine Learning and Robotics 2.0: With Live Raspberry Pi 3 Projects In Python 3.7

How to Use This Book
Machine learning fundamentally helps teach computers (through data, logic, and software) to “how to learn and what to do”. A machine learning program finds or discovers patterns in data and then behaves accordingly. We use Python throughout this book. It is a very simple language to learn, and it provides a lot of powerful features.
The first section of this book explains Machine Learning and Robotics 2.0. The second section of this book explains Advanced Chatbots with Python and Chatbots Design Principles. The third section of this book explains How to Set-up Raspberry Pi 3 and Working with Wireless USB. The fourth section of this book explains how to Create Rover Robot Car using Python and Robot Speech Recognition using Raspberry Pi 3.

Table of Contents
1.Machine Learning and Robotics 2.0
2.Recommendation Algorithms and Machine Learning
3.Robots and Artificial Intelligence
4.Python 3.7 Crash Course
5.Setting Up a Python Project
6.Static Typing in Python 3.7
7.Building Advanced Chatbots with Python
8.Advanced Bot Building Design Principles
9.Building an Adnavced Gaming Chatbot
10.How to Set-up Raspberry Pi 3?
11.Working with Wireless USB using Raspberry Pi 3
12.Create a Rover Robot Car using Python
13.Robot Speech Recognition using Raspberry Pi 3
14.NumPy and Pandas
15.Basic Introduction to Pygame
16.Working with Data using Python 3.7
17.Data Storage And Persistence Using Python 3.7
18.File I/O using Python 3.7
19.Machine Learning Application using Google Cloud Vision
20.File system in Raspberry Pi 3

Building Advanced Chatbots with Python
Chatbots, or conversational agents, are an exploding trend in AI and are seen as the next human interface with the computer. From Siri, Alexa, and Google Home, there has been an explosion of commercial growth in this area, and you most likely already have interfaced with a computer in this manner. Therefore, it only seems natural that we cover how to build conversational agents for games. For our purposes, however, we are going to look at the class of bots called neural conversational agents. Their name follows from the fact that they are developed with neural networks.

Create Rover Robot Car using Python
The goal of a Rover Robot Car Curiosity is basic scientific research, and in our case, there is the very important task of finding vestiges of any type of water on Mars, plus trying to remain active and avoid obstacles. A Rover Robot Car is an automated motor vehicle that is loaded up with cameras to analyze its surroundings, research instruments to dig in and maybe analyze interesting rocks, communication equipment with which to send pictures and data and receive commands, solar panels to provide energy to itself, and so on.

Robot Speech Recognition using Raspberry Pi 3
Teaching a robot to listen to spoken instructions is a whole discipline in itself. It is not sufficient for the robot to just recognize individual words or some canned phrase. We want the robot to respond to normal spoken commands with a normal variety of phrasing. We will be using a variety of techniques and processes for this chapter. We are going to be building on an open source verbal assistant called Mycroft. We will end up with a lot of collateral abilities for our robot that we are getting for free, and will end up with a very strong framework to build voice recognition and commands.

Machine Learning and Robotics 2.0
Machine learning is focused on using an advanced computational mechanism to develop dynamic algorithms that detect patterns in data, learn from experience, adjust programs, and improve accordingly.

The purpose of machine learning is to find meaningful simplicity and information/ insights in the midst of disordered complexity. It tries to optimize a performance criterion using past experience based on its learning.