This book will take you through all of the main aspects of artificial intelligence:
- The theory of machine learning and deep learning
- Mathematical representations of the main AI algorithms
- Real life case studies
- Tens of opensource Python programs using TensorFlow, TensorBoard, Keras and more
- Cloud AI Platforms: Google, Amazon Web Services, IBM Watson and IBM Q to introduce you to quantum computing
- An Ubuntu VM containing all the opensource programs that you can run in one-click
- Online videos
This book will take you to the cutting edge and beyond with innovations that show how to improve existing solutions to make you a key asset as a consultant, developer, professor or any person involved in artificial intelligence.
Who this book is for
- This book contains the main artificial intelligence algorithms on the market today. Each machine learning and deep learning solution is illustrated by a case study and an open source program available on GitHub.
- Project managers and consultants: To understand how to manage AI input datasets, make a solution choice (cloud platform or development), and use the outputs of an AI system.
- Teachers, students, and developers: This book provides an overview of many key AI components, with tens of Python sample programs that run on Windows and Linux. A VM is available as well.
- Anybody who wants to understand how AI systems are built and what they are used for.
Related posts:
Deep Learning for Natural Language Processing - Jason Brownlee
Neural Networks and Deep Learning - Charu C.Aggarwal
Python Machine Learning - Sebastian Raschka
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
The hundred-page Machine Learning Book - Andriy Burkov
Introduction to Deep Learning - Eugene Charniak
Deep Learning in Python - LazyProgrammer
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Medical Image Segmentation Using Artificial Neural Networks
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Data Science and Big Data Analytics - EMC Education Services
Machine Learning with Python for everyone - Mark E.Fenner
Pattern recognition and machine learning - Christopher M.Bishop
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Introduction to Scientific Programming with Python - Joakim Sundnes
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Deep Learning with Hadoop - Dipayan Dev
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Intelligent Projects Using Python - Santanu Pattanayak
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Machine Learning with spark and python - Michael Bowles
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
