Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniques

Table of Contents
Preface
Fundamentals of Robotics
	Introduction
	History of Robotics
	Artificial Intelligence
		Natural Language Processing
		Computer Vision
		Types of Robots
		Industrial Robots
		Service Robots
		Hardware and Software of Robots
	Robot Positioning
		Exercise 1: Computing a Robot’s Position
		How to Work with Robots
		Exercise 2: Computing the Distance Traveled by a Wheel with Python
		Exercise 3: Computing Final Position with Python
		Activity 1: Robot Positioning Using Odometry with Python
	Summary
Introduction to Computer Vision
	Introduction
	Basic Algorithms in Computer Vision
		Image Terminology
		OpenCV
		Basic Image Processing Algorithms
		Thresholding
		Exercise 4: Applying Various Thresholds to an Image
		Morphological Transformations
		Exercise 5: Applying the Various Morphological Transformations to an Image
		Blurring (Smoothing)
		Exercise 6: Applying the Various Blurring Methods to an Image
		Exercise 7: Loading an Image and Applying the Learned Methods
	Introduction to Machine Learning
		Decision Trees and Boosting Algorithms
		Bagging:
		Boosting
		Exercise 8: Predicting Numbers Using the Decision Tree, Random Forest, and AdaBoost Algorithms
		Artificial Neural Networks (ANNs)
		Exercise 9: Building Your First Neural Network
		Activity 2: Classify 10 Types of Clothes from the Fashion-MNIST Database
	Summary
Fundamentals of Natural Language Processing
	Introduction
		Natural Language Processing
		Parts of NLP
		Levels of NLP
	NLP in Python
		Natural Language Toolkit (NLTK)
		Exercise 10: Introduction to NLTK
		spaCy
		Exercise 11: Introduction to spaCy
	Topic Modeling
		Term Frequency – Inverse Document Frequency (TF-IDF)
		Latent Semantic Analysis (LSA)
		Exercise 12: Topic Modeling in Python
		Activity 3: Process a Corpus
	Language Modeling
		Introduction to Language Models
		The Bigram Model
		N-gram Model
		Calculating Probabilities
		Exercise 13: Create a Bigram Model
	Summary
Neural Networks with NLP
	Introduction
	Recurrent Neural Networks
		Introduction to Recurrent Neural Networks (RNN)
		Inside Recurrent Neural Networks
		RNN architectures
		Long-Dependency Problem
		Exercise 14: Predict House Prices with an RNN
	Long Short-Term Memory
		Exercise 15: Predict the Next Solution of a Mathematical Function
	Neural Language Models
		Introduction to Neural Language Models
		RNN Language Model
		Exercise 16: Encoding a Small Corpus
		The Input Dimensions of RNNs
		Activity 4: Predict the Next Character in a Sequence
	Summary
Convolutional Neural Networks for Computer Vision
	Introduction
	Fundamentals of CNNs
	Building Your First CNN
		Exercise 17: Building a CNN
	Improving Your Model - Data Augmentation
		Exercise 18: Improving Models Using Data Augmentation
		Activity 5: Making Use of Data Augmentation to Classify correctly Images of Flowers
	State-of-the-Art Models - Transfer Learning
		Exercise 19: Classifying €5 and €20 Bills Using Transfer Learning with Very Little Data
	Summary
Robot Operating System (ROS)
	Introduction
	ROS Concepts
	ROS Commands
	Installation and Configuration
	Catkin Workspaces and Packages
	Publishers and Subscribers
		Exercise 20: Publishing and Subscribing
		Exercise 21: Publishers and Subscribers
	Simulators
		Exercise 22: The Turtlebot configuration
		Exercise 23: Simulators and Sensors
		Activity 6: Simulators and Sensors
	Summary
Build a Text-Based Dialogue System (Chatbot)
	Introduction
	Word Representation in Vector Space
		Word Embeddings
		Cosine Similarity
		Word2Vec
		Problems with Word2Vec
		Gensim
		Exercise 24: Creation of a Word Embedding
		Global Vectors (GloVe)
		Exercise 25: Using a Pretrained GloVe to See the Distribution of Words in a Plane
	Dialogue Systems
		Tools for Developing Chatbots
		Types of Conversational Agents
		Classification by Input-Output Data Type
		Classification by System Knowledge
		Creation of a Text-Based Dialogue System
		Exercise 26: Create Your First Conversational Agent
		Activity 7: Create a Conversational Agent to Control a Robot
	Summary
Object Recognition to Guide a Robot Using CNNs
	Introduction
	Multiple Object Recognition and Detection
		Exercise 24: Building Your First Multiple Object Detection and Recognition Algorithm
		ImageAI
	Multiple Object Recognition and Detection in Video
		Activity 8: Multiple Object Detection and Recognition in Video
	Summary
Computer Vision for Robotics
	Introduction
	Darknet
		Basic Installation of Darknet
	YOLO
		First Steps in Image Classification with YOLO
		YOLO on a Webcam
		Exercise 28: Programming with YOLO
		ROS Integration
		Exercise 29: ROS and YOLO Integration
		Activity 9: A Robotic Security Guard
	Summary
Appendix
Index
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