Machine Learning Using TensorFlow Cookbook: Over 60 recipes on machine learning using deep learning solutions from Kaggle Masters and Google Developer
暫譯: 使用 TensorFlow 的機器學習食譜：超過 60 道來自 Kaggle 大師和 Google 開發者的深度學習解決方案食譜

Audevart, Alexia, Banachewicz, Konrad, Massaron, Luca

Machine Learning Using TensorFlow Cookbook: Over 60 recipes on machine learning using deep learning solutions from Kaggle Masters and Google Developer

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商品描述

Master TensorFlow to create powerful machine learning algorithms, with valuable insights on Keras, Boosted Trees, Tabular Data, Transformers, Reinforcement Learning and more

Key Features

  • Work with the latest code and examples for TensorFlow 2
  • Get to grips with the fundamentals including variables, matrices, and data sources
  • Learn advanced deep learning techniques to make your algorithms faster and more accurate

Book Description

The independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. You will work through recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google's machine learning library, TensorFlow.

This cookbook begins by introducing you to the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You'll then take a deep dive into some real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and for regression to provide a baseline for tabular data problems.

As you progress, you'll explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be applied to computer vision and natural language processing (NLP) problems. Once you are familiar with the TensorFlow ecosystem, the final chapter will teach you how to take a project to production.

By the end of this machine learning book, you will be proficient in using TensorFlow 2. You'll also understand deep learning from the fundamentals and be able to implement machine learning algorithms in real-world scenarios.

What you will learn

  • Grasp linear regression techniques with TensorFlow
  • Use Estimators to train linear models and boosted trees for classification or regression
  • Execute neural networks and improve predictions on tabular data
  • Master convolutional neural networks and recurrent neural networks through practical recipes
  • Apply reinforcement learning algorithms using the TF-Agents framework
  • Implement and fine-tune Transformer models for various NLP tasks
  • Take TensorFlow into production

Who this book is for

If you are a data scientist or a machine learning engineer, and you want to skip detailed theoretical explanations in favor of building production-ready machine learning models using TensorFlow, this book is for you.

Basic familiarity with Python, linear algebra, statistics, and machine learning is necessary to make the most out of this book.

商品描述(中文翻譯)

**掌握 TensorFlow 以創建強大的機器學習算法，並獲得有關 Keras、增強樹、表格數據、變壓器、強化學習等的寶貴見解**

#### 主要特點

- 使用最新的 TensorFlow 2 代碼和範例
- 理解基本概念，包括變數、矩陣和數據來源
- 學習先進的深度學習技術，使您的算法更快且更準確

#### 書籍描述

《使用 TensorFlow 食譜進行機器學習》中的獨立食譜將教您如何執行複雜的數據計算並獲得對數據的寶貴見解。您將通過訓練模型、模型評估、情感分析、回歸分析、人工神經網絡和深度學習的食譜進行學習，每個食譜都使用 Google 的機器學習庫 TensorFlow。

本食譜首先介紹 TensorFlow 庫的基本概念，包括變數、矩陣和各種數據來源。然後，您將深入了解 Keras 和 TensorFlow 的一些實際應用，學習如何使用估計器訓練線性模型和增強樹，無論是用於分類還是回歸，以提供表格數據問題的基準。

隨著進度的推進，您將探索各種深度學習架構的實際應用，例如循環神經網絡和變壓器，並了解它們如何應用於計算機視覺和自然語言處理（NLP）問題。一旦您熟悉 TensorFlow 生態系統，最後一章將教您如何將項目投入生產。

到本書結束時，您將熟練使用 TensorFlow 2。您還將從基本概念理解深度學習，並能夠在現實場景中實施機器學習算法。

#### 您將學到的內容

- 掌握使用 TensorFlow 的線性回歸技術
- 使用估計器訓練線性模型和增強樹以進行分類或回歸
- 執行神經網絡並改善表格數據的預測
- 通過實用食譜掌握卷積神經網絡和循環神經網絡
- 使用 TF-Agents 框架應用強化學習算法
- 實施和微調變壓器模型以應對各種 NLP 任務
- 將 TensorFlow 應用於生產

#### 本書適合誰

如果您是數據科學家或機器學習工程師，並希望跳過詳細的理論解釋，專注於使用 TensorFlow 構建生產就緒的機器學習模型，那麼這本書適合您。

基本熟悉 Python、線性代數、統計學和機器學習是充分利用本書的必要條件。

作者簡介

Alexia Audevart, also a Google Developer Expert in machine learning, is the founder of datactik. She is a data scientist and helps her clients solve business problems by making their applications smarter. Her first book is a collaboration on artificial intelligence and neuroscience.

Konrad Banachewicz holds a PhD in statistics from Vrije Universiteit Amsterdam. He is a lead data scientist at eBay and a Kaggle Grandmaster. He worked in a variety of financial institutions on a wide array of quantitative data analysis problems. In the process, he became an expert on the entire lifetime of a data product cycle.

Luca Massaron is a Google Developer Expert in machine learning with more than a decade of experience in data science. He is also the author of several best-selling books on AI and a Kaggle master who reached number 7 for his performance in data science competitions.

作者簡介(中文翻譯)

Alexia Audevart，也是一位專注於機器學習的 Google 開發者專家，是 datactik 的創辦人。她是一名數據科學家，幫助客戶通過使其應用程序更智能來解決商業問題。她的第一本書是關於人工智慧和神經科學的合作作品。

Konrad Banachewicz 擁有阿姆斯特丹自由大學的統計學博士學位。他是 eBay 的首席數據科學家，也是 Kaggle 大師。他曾在多家金融機構工作，處理各種定量數據分析問題。在此過程中，他成為數據產品生命周期的專家。

Luca Massaron 是一位擁有超過十年數據科學經驗的 Google 開發者專家，專注於機器學習。他也是幾本關於人工智慧的暢銷書作者，並且是一位 Kaggle 大師，在數據科學競賽中達到第七名的表現。

目錄大綱

  1. Getting Started with TensorFlow 2.x
  2. The TensorFlow Way
  3. Keras
  4. Linear Regression
  5. Boosted Trees
  6. Neural Networks
  7. Predicting with Tabular Data
  8. Convolutional Neural Networks
  9. Recurrent Neural Networks
  10. Transformers
  11. Reinforcement Learning with TensorFlow and TF-Agents
  12. Taking TensorFlow to Production

目錄大綱(中文翻譯)


  1. Getting Started with TensorFlow 2.x

  2. The TensorFlow Way

  3. Keras

  4. Linear Regression

  5. Boosted Trees

  6. Neural Networks

  7. Predicting with Tabular Data

  8. Convolutional Neural Networks

  9. Recurrent Neural Networks

  10. Transformers

  11. Reinforcement Learning with TensorFlow and TF-Agents

  12. Taking TensorFlow to Production

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