Beginning Anomaly Detection Using Python-Based Deep Learning: With Keras and Pytorch

Alla, Sridhar, Adari, Suman Kalyan

Beginning Anomaly Detection Using Python-Based Deep Learning: With Keras and Pytorch

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商品描述

Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks.
This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semi-supervised anomaly detection along with the basics of time series-based anomaly detection.
By the end of the book you will have a thorough understanding of the basic task of anomaly detection as well as an assortment of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to Scikit-Learn and are able to create deep learning models in Keras and PyTorch.

What You Will Learn

  • Understand what anomaly detection is and why it is important in today's world
  • Become familiar with statistical and traditional machine learning approaches to anomaly detection using Scikit-Learn
  • Know the basics of deep learning in Python using Keras and PyTorch
  • Be aware of basic data science concepts for measuring a model's performance: understand what AUC is, what precision and recall mean, and more
  • Apply deep learning to semi-supervised and unsupervised anomaly detection


Who This Book Is For
Data scientists and machine learning engineers interested in learning the basics of deep learning applications in anomaly detection

商品描述(中文翻譯)

利用這本易於理解的初學者指南，了解深度學習如何應用於異常檢測任務。本書使用Python中的Keras和PyTorch，重點介紹了如何將各種深度學習模型應用於半監督和無監督的異常檢測任務。

本書首先解釋了異常檢測的定義、用途和重要性。在使用Python中的Scikit-Learn介紹統計和傳統機器學習方法進行異常檢測之後，本書詳細介紹了如何在Keras和PyTorch中構建和訓練深度學習模型，然後將重點轉向以下深度學習模型在異常檢測中的應用：各種類型的自編碼器、受限玻爾茲曼機、循環神經網絡和長短期記憶網絡，以及時間卷積網絡。本書還探討了無監督和半監督的異常檢測，以及基於時間序列的異常檢測的基礎知識。

通過閱讀本書，您將全面了解異常檢測的基本任務，以及從傳統方法到深度學習的各種方法。此外，您還將介紹Scikit-Learn，並能夠在Keras和PyTorch中創建深度學習模型。

您將學到什麼：
- 了解異常檢測的定義以及在當今世界中的重要性
- 熟悉使用Scikit-Learn進行異常檢測的統計和傳統機器學習方法
- 了解使用Keras和PyTorch進行Python中的深度學習的基礎知識
- 了解衡量模型性能的基本數據科學概念：了解AUC是什麼，了解精確度和召回率等等
- 將深度學習應用於半監督和無監督的異常檢測

本書適合對深度學習在異常檢測中的基礎應用感興趣的數據科學家和機器學習工程師。

作者簡介

Sridhar Alla is the co-founder and CTO of Bluewhale, which helps organizations big and small in building AI-driven big data solutions and analytics. He is a published author of books and an avid presenter at numerous Strata, Hadoop World, Spark Summit, and other conferences. He also has several patents filed with the US PTO on large-scale computing and distributed systems. He has extensive hands-on experience in several technologies, including Spark, Flink, Hadoop, AWS, Azure, Tensorflow, Cassandra, and others. He spoke on Anomaly Detection Using Deep Learning at Strata SFO in March 2019 and will also present at Strata London in October 2019. He was born in Hyderabad, India and now lives in New Jersey, USA with his wife Rosie and daughter Evelyn. When he is not busy writing code, he loves to spend time with his family and also training, coaching, and organizing meetups.

Suman Kalyan Adari is an undergraduate student pursuing a BS degree in Computer Science at the University of Florida. He has been conducting deep learning research in the field of cybersecurity since his freshman year, and has presented at the IEEE Dependable Systems and Networks workshop on Dependable and Secure Machine Learning held in Portland, Oregon, USA in June 2019. He is quite passionate about deep learning, and specializes in its practical uses in various fields such as video processing, image recognition, anomaly detection, targeted adversarial attacks, and more.

作者簡介(中文翻譯)

Sridhar Alla是Bluewhale的聯合創始人和首席技術官（CTO），該公司幫助各種規模的組織建立基於人工智慧的大數據解決方案和分析。他是一位出版書籍的作者，並在許多Strata、Hadoop World、Spark Summit和其他會議上擔任熱情的演講者。他在美國專利商標局（US PTO）申請了多項關於大規模計算和分散系統的專利。他在多個技術領域擁有豐富的實踐經驗，包括Spark、Flink、Hadoop、AWS、Azure、Tensorflow、Cassandra等。他在2019年3月的Strata SFO會議上演講了有關使用深度學習進行異常檢測的主題，並將在2019年10月的Strata London會議上再次演講。他出生於印度海得拉巴，現與妻子Rosie和女兒Evelyn居住在美國新澤西州。當他不忙於編寫代碼時，他喜歡與家人共度時光，並參與培訓、指導和組織聚會。

Suman Kalyan Adari是佛羅里達大學計算機科學學士學位的本科生。自他大一開始，他一直在進行深度學習在網絡安全領域的研究，並在2019年6月在美國俄勒岡州波特蘭舉行的IEEE可靠系統和網絡研討會上發表了有關可靠和安全機器學習的演講。他對深度學習非常熱衷，專注於其在視頻處理、圖像識別、異常檢測、有針對性的對抗攻擊等各個領域的實際應用。

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