Predictive Analytics with TensorFlow. Implement deep learning principles to predict valuable insights using TensorFlow Md. Rezaul Karim

About This BookA quick guide to gain hands-on experience with deep learning in different domains such as digit/image classification, and textsBuild your own smart, predictive models with TensorFlow using easy-to-follow approach mentioned in the bookUnderstand deep learning and predictive analytics along with its challenges and best practicesWho This Book Is ForThis book is intended for anyone who wants to build predictive models with the power of TensorFlow from scratch. If you want to build your own extensive applications which work, and can predict smart decisions in the future then this book is what you need!What You Will LearnSolid & theoretical understanding of linear algebra, statistics & probability for predictive modelingDevelop predictive models using classification, regression & clustering algorithmsDevelop predictive models for NLPReinforcement learning for predictive analyticsFactorization Machines for advanced recommendation systemsHands-on understanding of deep learning architectures for advanced predictive analyticsDeep Neural Networks for predictive analyticsRecurrent Neural Networks for predictive analyticsConvolutional Neural Networks for emotion recognition, image classification & sentiment analysis.In DetailPredictive analytics allows discovering hidden patterns from structured & unstructured data for automated decision making in business intelligence.This book will help you build, tune & deploy predictive models with TensorFlow in three main sections. The first section covers linear algebra, statistics & probability theory for predictive modeling.The second section shows developing predictive models via supervised (classification, regression) & unsupervised (clustering) algorithms. It then exhibits developing predictive models for NLP and covers reinforcement learning algorithms. Lastly, developing a Factorization Machines-based recommendation system is shown.The third section covers deep learning architectures for advanced predictive analytics: including, Deep Neural Networks & Recurrent Neural Networks for high-dimensional and sequence data. Finally, Convolutional Neural Networks is used for predictive modeling for emotion recognition, image classification & sentiment analysis. Это и многое другое вы найдете в книге Predictive Analytics with TensorFlow. Implement deep learning principles to predict valuable insights using TensorFlow (Md. Rezaul Karim)