TensorFlow : powerful predictive analytics with TensorFlow : rapid learning solution

TensorFlow : powerful predictive analytics with TensorFlow : rapid learning solution / Md. Rezaul Karim.

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Bibliografiske detaljer
Hovedforfatter: Karim, Md. Rezaul (Author)
Format: eBog
Sprog:English
Udgivet: Birmingham : Packt Publishing, 2018.
Fag:
Open source software > Library applications.
Open source software.
COMPUTER SCIENCE > General.
Open source software
Open source software > Library applications
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Indholdsfortegnelse:
  • Intro; Title Page; Copyright; Credits; Table of Contents; Preface; Lesson 1: From Data to Decisions â#x80;#x93; Getting Started with TensorFlow; Taking Decisions Based on Data â#x80;#x93; Titanic Example; Data Value Chain for Making Decisions; From Disaster to Decision â#x80;#x93; Titanic Survival Example; General Overview of TensorFlow; Installing and Configuring TensorFlow; Installing TensorFlow on Linux; Installing Python and nVidia Driver; Installing NVIDIA CUDA; Installing NVIDIA cuDNN v5.1+; Installing the libcupti-dev Library; Installing TensorFlow; Installing TensorFlow from Source.
  • Testing Your TensorFlow InstallationTensorFlow Computational Graph; TensorFlow Programming Model; Data Model in TensorFlow; Tensors; Rank; Shape; Data Type; Variables; Fetches; Feeds and Placeholders; TensorBoard; How Does TensorBoard Work?; Getting Started with TensorFlow â#x80;#x93; Linear Regression and Beyond; Source Code for the Linear Regression; Summary; Assessments; Lesson 2: Putting Data in Place â#x80;#x93; Supervised Learning for Predictive Analytics; Supervised Learning for Predictive Analytics; Linear Regression â#x80;#x93; Revisited; Problem Statement.
  • Using Linear Regression for Movie Rating PredictionFrom Disaster to Decision â#x80;#x93; Titanic Example Revisited; An Exploratory Analysis of the Titanic Dataset; Feature Engineering; Logistic Regression for Survival Prediction; Using TensorFlow Contrib; Linear SVM for Survival Prediction; Ensemble Method for Survival Prediction â#x80;#x93; Random Forest; A Comparative Analysis; Summary; Assessments; Lesson 3: Clustering Your Data â#x80;#x93; Unsupervised Learning for Predictive Analytics; Unsupervised Learning and Clustering; Using K-means for Predictive Analytics; How K-means Works.
  • Using K-means for Predicting NeighborhoodsPredictive Models for Clustering Audio Files; Using kNN for Predictive Analytics; Working Principles of kNN; Implementing a kNN-Based Predictive Model; Summary; Assessments; Lesson 4: Using Reinforcement Learning for Predictive Analytics; Reinforcement Learning; Reinforcement Learning in Predictive Analytics; Notation, Policy, and Utility in RL; Policy; Utility; Developing a Multiarmed Bandit's Predictive Model; Developing a Stock Price Predictive Model; Summary; Assessments; Appendix: Assessment Answers.

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