Giuseppe Ciaburro

Keras Reinforcement Learning Projects (eBook, ePUB)

9 projects exploring popular reinforcement learning techniques to build self-learning agents

• Format: ePub

Produktbeschreibung

Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library.

The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You’ll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You’ll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes.

Once you’ve understood the basics, you’ll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning, and building a handwritten digit recognition model in Python using an image dataset. Finally, you’ll excel in playing the board game Go with the help of Q-Learning and reinforcement learning algorithms.

By the end of this book, you’ll not only have developed hands-on training on concepts, algorithms, and techniques of reinforcement learning but also be all set to explore the world of AI.

Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 288
• Erscheinungstermin: 29. September 2018
• Englisch
• ISBN-13: 9781789347975
• Artikelnr.: 54272837

Autorenporträt

Giuseppe Ciaburro holds a PhD in environmental technical physics, along with two master's degrees holds a master's degree in chemical engineering from Università degli Studi di Napoli Federico II, and a master's degreeand in acoustic and noise control from Seconda Università degli Studi di Napoli. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli".He has over 15 20 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in Python and R, and he has extensive experience of working with MATLAB. An expert in acoustics and noise control, Giuseppe has wide experience in teaching professional computer ITC courses (about 15 20 years), dealing with e-learning as an author. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He is currently researching machine learning applications in acoustics and noise control. He was recently included in the world's top 2% scientists list by Stanford University.