Python: Beginner’s Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Python: Beginner’s Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Python: Beginner’s Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
By 作者: Denis Rothman – Matthew Lamons – Rahul Kumar – Abhishek Nagaraja – Amir Ziai – Ankit Dixit
ISBN-10 书号: 178995732X
ISBN-13 书号: 9781789957327
Release Finelybook 出版日期: 2018-12-24
pages 页数: (676 )

$49.99


Book Description to Finelybook sorting

This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. You’ll find a new balance of classical ideas and modern insights into machine learning. You will learn to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open-source Python libraries.

Throughout the Learning Path, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and Autoencoders. Discover how to attain deep learning programming on GPU in a distributed way.

By the end of this Learning Path, you know the fundamentals of AI and have worked through a number of case studies that will help you apply your skills to real-world projects.

This Learning Path includes content from the following Packt products:

Artificial Intelligence By Example by Denis Rothman
Python Deep Learning Projects by Matthew Lamons, Rahul Kumar, and Abhishek Nagaraja
Hands-On Artificial Intelligence with TensorFlow by Amir Ziai, Ankit Di

Contents
1: BECOME AN ADAPTIVE THINKER
2: THINK LIKE A MACHINE
3: APPLY MACHINE THINKING TO A HUMAN PROBLEM
4: BECOME AN UNCONVENTIONAL INNOVATOR
5: MANAGE THE POWER OF MACHINE LEARNING AND DEEP LEARNING
6: FOCUS ON OPTIMIZING YOUR SOLUTIONS
7: WHEN AND HOW TO USE ARTIFICIAL INTELLIGENCE
8: REVOLUTIONS DESIGNED FOR SOME CORPORATIONS AND DISRUPTIVE INNOVATIONS FOR SMALL TO LARGE COMPANIES
9: GETTING YOUR NEURONS TO WORK
10: APPLYING BIOMIMICKING TO ARTIFICIAL INTELLIGENCE
11: CONCEPTUAL REPRESENTATION LEARNING
12: OPTIMIZING BLOCKCHAINS WITH AI
13: COGNITIVE NLP CHATBOTS
14: IMPROVE THE EMOTIONAL INTELLIGENCE DEFICIENCIES OF CHATBOTS
15: BUILDING DEEP LEARNING ENVIRONMENTS
16: TRAINING NN FOR PREDICTION USING REGRESSION
17: GENERATIVE LANGUAGE MODEL FOR CONTENT CREATION
18: BUILDING SPEECH RECOGNITION WITH DEEPSPEECH2
19: HANDWRITTEN DIGITS CLASSIFICATION USING CONVNETS
20: OBJECT DETECTION USING OPENCV AND TENSORFLOW
21: BUILDING FACE RECOGNITION USING FACENET
22: GENERATIVE ADVERSARIAL NETWORKS
23: FROM GPUS TO QUANTUM COMPUTING – AI HARDWARE
24: TENSORFLOW SERVING
What You Will Learn
Use adaptive thinking to solve real-life AI case studies
Rise beyond being a modern-day factory code worker
Understand future AI solutions and adapt quickly to them
Master deep neural network implementation using TensorFlow
Predict continuous target outcomes using regression analysis
Dive deep into textual and social media data using sentiment analysis
Authors
Denis Rothman
Denis Rothman graduated from l’Université Paris-Sorbonne and l’Université Paris-Diderot, writing one of the very first word2matrix embedding solutions. He began his career authoring one of the first AI cognitive NLP chatbots applied as a language teacher for Moët et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.

Matthew Lamons
Matthew Lamons’s background is in experimental psychology and deep learning. Founder and CEO of Skejul—the AI platform to help people manage their activities. Named by Gartner, Inc. as a “Cool Vendor” in the “Cool Vendors in Unified Communication, 2017” report. He founded The Intelligence Factory to build AI strategy, solutions, insights, and talent for enterprise clients and incubate AI tech startups based on the success of his Applied AI MasterMinds group. Matthew’s global community of more than 85 K are leaders in AI, forecasting, robotics, autonomous vehicles, marketing tech, NLP, computer vision, reinforcement, and deep learning. Matthew invites you to join him on his mission to simplify the future and to build AI for good.

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