Beginning Mlops with Mlflow: Deploy Models in Aws Sagemaker, Google Cloud, and Microsoft Azure (從零開始的 MLOps：使用 MLflow 在 AWS Sagemaker、Google Cloud 和 Microsoft Azure 部署模型)

Alla, Sridhar, Adari, Suman Kalyan

Beginning Mlops with Mlflow: Deploy Models in Aws Sagemaker, Google Cloud, and Microsoft Azure
  • 出版商: Apress
  • 出版日期: 2020-12-08
  • 售價: $2,330
  • 貴賓價: 9.5 折 $2,214
  • 語言: 英文
  • 頁數: 330
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484265483
  • ISBN-13: 9781484265482
  • 相關分類: Amazon Web Services、Google Cloud、Maker、Microsoft Azure

    • 海外代購書籍(需單獨結帳)

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商品描述

Integrate MLOps principles into existing or future projects using MLFlow, operationalize your models, and deploy them in AWS SageMaker, Google Cloud, and Microsoft Azure. ​This book guides you through the process of data analysis, model construction, and training.
The authors begin by introducing you to basic data analysis on a credit card data set and teach you how to analyze the features and their relationships to the target variable. You will learn how to build logistic regression models in scikit-learn and PySpark, and you will go through the process of hyperparameter tuning with a validation data set. You will explore three different deployment setups of machine learning models with varying levels of automation to help you better understand MLOps. MLFlow is covered and you will explore how to integrate MLOps into your existing code, allowing you to easily track metrics, parameters, graphs, and models. You will be guided through the process of deploying and querying your models with AWS SageMaker, Google Cloud, and Microsoft Azure. And you will learn how to integrate your MLOps setups using Databricks.

 

 

What You Will Learn

 

  • Perform basic data analysis and construct models in scikit-learn and PySpark
  • Train, test, and validate your models (hyperparameter tuning)
  • Know what MLOps is and what an ideal MLOps setup looks like
  • Easily integrate MLFlow into your existing or future projects
  • Deploy your models and perform predictions with them on the cloud

 

 

Who This Book Is For
Data scientists and machine learning engineers who want to learn MLOps and know how to operationalize their models

商品描述(中文翻譯)

將 MLOps 原則整合到現有或未來的專案中，使用 MLFlow，將您的模型運營化，並在 AWS SageMaker、Google Cloud 和 Microsoft Azure 上部署它們。本書將指導您完成數據分析、模型構建和訓練的過程。

作者首先介紹了如何在信用卡數據集上進行基本的數據分析，並教您如何分析特徵及其與目標變數的關係。您將學習如何在 scikit-learn 和 PySpark 中構建邏輯回歸模型，並通過驗證數據集進行超參數調整。您將探索三種不同的機器學習模型部署設置，這些設置具有不同程度的自動化，以幫助您更好地理解 MLOps。本書涵蓋了 MLFlow，您將探索如何將 MLOps 整合到現有代碼中，讓您輕鬆追蹤指標、參數、圖表和模型。您將被指導如何在 AWS SageMaker、Google Cloud 和 Microsoft Azure 上部署和查詢您的模型。您還將學習如何使用 Databricks 整合您的 MLOps 設置。

您將學到的內容：

- 執行基本數據分析並在 scikit-learn 和 PySpark 中構建模型
- 訓練、測試和驗證您的模型（超參數調整）
- 知道什麼是 MLOps 以及理想的 MLOps 設置是什麼樣子
- 輕鬆將 MLFlow 整合到現有或未來的專案中
- 在雲端部署您的模型並進行預測

本書適合對象：

希望學習 MLOps 並了解如何將模型運營化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 big and small organizations build 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 of 2019 and at Strata London in October of 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 of 2019. He is passionate about deep learning, and specializes in its practical uses in various fields such as image recognition, anomaly detection, natural language processing, targeted adversarial attacks, and more.

作者簡介(中文翻譯)

Sridhar Alla 是 Bluewhale 的共同創辦人及首席技術官，該公司協助大小型組織建立以 AI 驅動的大數據解決方案和分析。他是多本書籍的出版作者，並在多個 Strata、Hadoop World、Spark Summit 及其他會議上積極演講。他在大型計算和分散式系統方面擁有多項專利，並已向美國專利商標局申請。他在多種技術上擁有豐富的實務經驗，包括 Spark、Flink、Hadoop、AWS、Azure、Tensorflow、Cassandra 等。他於 2019 年 3 月在 Strata SFO 和 2019 年 10 月在 Strata London 發表了關於使用深度學習進行異常檢測的演講。他出生於印度海得拉巴，現在與妻子 Rosie 和女兒 Evelyn 住在美國新澤西州。當他不忙於編寫程式碼時，他喜歡與家人共度時光，並進行訓練、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。他自大一以來便在網路安全領域進行深度學習研究，並於 2019 年 6 月在美國俄勒岡州波特蘭舉行的 IEEE 可靠系統與網路研討會上發表了關於可靠和安全機器學習的演講。他對深度學習充滿熱情，專注於其在圖像識別、異常檢測、自然語言處理、針對性對抗攻擊等各個領域的實際應用。

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