Building Machine Learning Projects with TensorFlow (Paperback)

Rodolfo Bonnin

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商品描述

Key Features

  • Bored of too much theory on TensorFlow? This book is what you need! Thirteen solid projects and four examples teach you how to implement TensorFlow in production.
  • This example-rich guide teaches you how to perform highly accurate and efficient numerical computing with TensorFlow
  • It is a practical and methodically explained guide that allows you to apply Tensorflow’s features from the very beginning.

Book Description

This book of projects highlights how TensorFlow can be used in different scenarios - this includes projects for training models, machine learning, deep learning, and working with various neural networks. Each project provides exciting and insightful exercises that will teach you how to use TensorFlow and show you how layers of data can be explored by working with Tensors. Simply pick a project that is in line with your environment and get stacks of information on how to implement TensorFlow in production.

What you will learn

  • Load, interact, dissect, process, and save complex datasets
  • Solve classification and regression problems using state of the art techniques
  • Predict the outcome of a simple time series using Linear Regression modeling
  • Use a Logistic Regression scheme to predict the future result of a time series
  • Classify images using deep neural network schemes
  • Tag a set of images and detect features using a deep neural network, including a Convolutional Neural Network (CNN) layer
  • Resolve character recognition problems using the Recurrent Neural Network (RNN) model

About the Author

Rodolfo Bonnin is a systems engineer and PhD student at Universidad Tecnológica Nacional, Argentina. He also pursued parallel programming and image understanding postgraduate courses at Uni Stuttgart, Germany.

He has done research on high performance computing since 2005 and began studying and implementing convolutional neural networks in 2008,writing a CPU and GPU - supporting neural network feed forward stage. More recently he's been working in the field of fraud pattern detection with Neural Networks, and is currently working on signal classification using ML techniques.

Table of Contents

  1. Exploring and Transforming Data
  2. Clustering
  3. Linear Regression
  4. Logistic Regression
  5. Simple FeedForward Neural Networks
  6. Convolutional Neural Networks
  7. Recurrent Neural Networks and LSTM
  8. Deep Neural Networks
  9. Running Models at Scale – GPU and Serving
  10. Library Installation and Additional Tips

商品描述(中文翻譯)

主要特點


  • 厭倦了關於TensorFlow的太多理論嗎?這本書正是你需要的!十三個實用的專案和四個範例教你如何在實際應用中使用TensorFlow。

  • 這本範例豐富的指南教你如何使用TensorFlow進行高精度和高效的數值計算。

  • 這是一本實用且有系統解釋的指南,讓你從一開始就能應用TensorFlow的功能。

書籍描述

這本專案書突出了TensorFlow在不同場景中的應用,包括模型訓練、機器學習、深度學習以及與各種神經網絡的合作。每個專案都提供了令人興奮且有深度的練習,教你如何使用TensorFlow並展示如何通過處理Tensor來探索數據的層次。只需選擇一個符合你環境的專案,就能獲得大量有關如何在實際應用中實現TensorFlow的信息。

你將學到什麼


  • 加載、交互、解析、處理和保存複雜數據集

  • 使用最先進的技術解決分類和回歸問題

  • 使用線性回歸模型預測簡單時間序列的結果

  • 使用邏輯回歸模型預測時間序列的未來結果

  • 使用深度神經網絡方案對圖像進行分類

  • 使用深度神經網絡標記一組圖像並檢測特徵,包括卷積神經網絡(CNN)層

  • 使用循環神經網絡(RNN)模型解決字符識別問題

關於作者

Rodolfo Bonnin是阿根廷國立技術大學的系統工程師和博士生。他還在德國斯圖加特大學進修了並行編程和圖像理解的研究生課程。

他從2005年開始從事高性能計算的研究,並於2008年開始研究和實現卷積神經網絡,撰寫了一個支持CPU和GPU的神經網絡前向階段。最近,他一直在使用神經網絡領域中的詐騙模式檢測,目前正在使用機器學習技術進行信號分類的研究。

目錄


  1. 探索和轉換數據

  2. 聚類

  3. 線性回歸

  4. 邏輯回歸

  5. 簡單前饋神經網絡

  6. 卷積神經網絡

  7. 循環神經網絡和LSTM

  8. 深度神經網絡

  9. 在規模上運行模型 - GPU和服務

  10. 庫安裝和其他技巧