- Series Introduction
- Example Computer Languages
- Prerequisite Knowledge
- Fundamental Algorithms
- Other Resources
- Structure of this Book
This book is the third in a series covering select topics in artificial intelligence (AI), a large field of study that encompasses many sub-disciplines. In this introduction, we will provide some background information for readers who might not have read Volume 1 or 2.
It is not necessary to read Volume 1 or 2 before this book. We introduce needed information from both volumes in the following sections.
Related posts:
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Intelligent Projects Using Python - Santanu Pattanayak
Python Machine Learning - Sebastian Raschka
Introduction to Scientific Programming with Python - Joakim Sundnes
Neural Networks - A visual introduction for beginners - Michael Taylor
Medical Image Segmentation Using Artificial Neural Networks
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Artificial Intelligence by example - Denis Rothman
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Deep Learning with PyTorch - Vishnu Subramanian
Deep Learning with Hadoop - Dipayan Dev
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Introduction to Deep Learning - Eugene Charniak
Python Data Structures and Algorithms - Benjamin Baka
Introduction to the Math of Neural Networks - Jeff Heaton
Python Machine Learning Eqution Reference - Sebastian Raschka
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning for Natural Language Processing - Jason Brownlee
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
