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" Methods of Fundamental Solutions in Solid Mechanics / "


Document Type : BL
Record Number : 856601
Main Entry : Rothman, Denis
Title & Author : Artificial intelligence by example : : develop machine intelligence from scratch using real artificial intelligence use cases /\ Denis Rothman.
Publication Statement : Birmingham :: Packt Publishing,, [2018]
: , ©2018
Page. NO : 1 online resource (xi, 458 pages)
ISBN : 1788990021
: : 1788990544
: : 9781788990028
: : 9781788990547
: 9781788990547
Notes : Using TensorBoard to explain the concept of classifying customer products to a CEO.
Bibliographies/Indexes : Includes bibliographical references, webology and index.
Contents : Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Become an Adaptive Thinker; Technical requirements; How to be an adaptive thinker; Addressing real-life issues before coding a solution; Step 1 -- MDP in natural language; Step 2 -- the mathematical representation of the Bellman equation and MDP; From MDP to the Bellman equation; Step 3 -- implementing the solution in Python; The lessons of reinforcement learning; How to use the outputs; Machine learning versus traditional applications; Summary; Questions; Further reading.
: Chapter 2: Think like a MachineTechnical requirements; Designing datasets -- where the dream stops and the hard work begins; Designing datasets in natural language meetings; Using the McCulloch-Pitts neuron ; The McCulloch-Pitts neuron; The architecture of Python TensorFlow; Logistic activation functions and classifiers; Overall architecture; Logistic classifier; Logistic function; Softmax; Summary; Questions; Further reading; Chapter 3: Apply Machine Thinking to a Human Problem; Technical requirements; Determining what and how to measure; Convergence; Implicit convergence.
: Numerical -- controlled convergenceApplying machine thinking to a human problem; Evaluating a position in a chess game; Applying the evaluation and convergence process to a business problem; Using supervised learning to evaluate result quality; Summary; Questions; Further reading; Chapter 4: Become an Unconventional Innovator; Technical requirements; The XOR limit of the original perceptron; XOR and linearly separable models; Linearly separable models; The XOR limit of a linear model, such as the original perceptron; Building a feedforward neural network from scratch.
: Step 1 -- Defining a feedforward neural networkStep 2 -- how two children solve the XOR problem every day; Implementing a vintage XOR solution in Python with an FNN and backpropagation; A simplified version of a cost function and gradient descent; Linear separability was achieved; Applying the FNN XOR solution to a case study to optimize subsets of data; Summary; Questions; Further reading; Chapter 5: Manage the Power of Machine Learning and Deep Learning; Technical requirements; Building the architecture of an FNN with TensorFlow.
: Writing code using the data flow graph as an architectural roadmapA data flow graph translated into source code; The input data layer; The hidden layer; The output layer; The cost or loss function; Gradient descent and backpropagation; Running the session; Checking linear separability; Using TensorBoard to design the architecture of your machine learning and deep learning solutions; Designing the architecture of the data flow graph; Displaying the data flow graph in TensorBoard; The final source code with TensorFlow and TensorBoard; Using TensorBoard in a corporate environment.
Abstract : Artificial Intelligence(AI), gets your system to think smart and intelligent. This book is packed with some of the smartest and easy-peasy examples through which you will learn the fundamentals of AI. You will have acquired the foundation of AI and understood the practical case studies in this book.
Subject : Application software-- Development.
Subject : Artificial intelligence-- Data processing.
Subject : Cloud computing.
Subject : Python (Computer program language)
Subject : Application software-- Development.
copyhttps://lib.clisel.com/site/catalogue/872554
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