Python: Advanced Guide to Artificial Intelligence PDF
By:Giuseppe Bonaccorso,Armando Fandango,Rajalingappaa Shanmugamani
Published on 2018-12-21 by Packt Publishing Ltd
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Mastering TensorFlow 1.x by Armando Fandango Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn Explore how an ML model can be trained, optimized, and evaluated Work with Autoencoders and Generative Adversarial Networks Explore the most important Reinforcement Learning techniques Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
This Book was ranked at 28 by Google Books for keyword Computer Science AI Machine Learning Computers Technology.
Book ID of Python: Advanced Guide to Artificial Intelligence's Books is GtCBDwAAQBAJ, Book which was written byGiuseppe Bonaccorso,Armando Fandango,Rajalingappaa Shanmugamanihave ETAG "4z3sPqjbFdQ"
Book which was published by Packt Publishing Ltd since 2018-12-21 have ISBNs, ISBN 13 Code is 9781789951721 and ISBN 10 Code is 1789951720
Reading Mode in Text Status is true and Reading Mode in Image Status is true
Book which have "764 Pages" is Printed at BOOK under CategoryComputers
Book was written in en
eBook Version Availability Status at PDF is trueand in ePub is true
Book Preview
Download Python: Advanced Guide to Artificial Intelligence PDF Free
Download Python: Advanced Guide to Artificial Intelligence Book Free
Download Python: Advanced Guide to Artificial Intelligence Free
Download Python: Advanced Guide to Artificial Intelligence PDF
Download Python: Advanced Guide to Artificial Intelligence Book
How to Download Python: Advanced Guide to Artificial Intelligence Book
How to Download Python: Advanced Guide to Artificial Intelligence
How to Download Python: Advanced Guide to Artificial Intelligence pdf
How to Download Python: Advanced Guide to Artificial Intelligence free
Free Download Python: Advanced Guide to Artificial Intelligence
No comments:
Post a Comment