Machine Learning with Microsoft Technologies: Selecting the Right Architecture and Tools for Your Project

Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more.

The ability to analyze massive amounts of real-time data and predict future behavior of an organization is critical to its long-term success. Data science, and more specifically machine learning (ML), is today's game changer and should be a key building block in every company's strategy. Managing a machine learning process from business understanding, data acquisition and cleaning, modeling, and deployment in each tool is a valuable skill set.

Machine Learning with Microsoft Technologies is a demo-driven book that explains how to do machine learning with Microsoft technologies. You will gain valuable insight into designing the best architecture for development, sharing, and deploying a machine learning solution. This book simplifies the process of choosing the right architecture and tools for doing machine learning based on your specific infrastructure needs and requirements.

Detailed content is provided on the main algorithms for supervised and unsupervised machine learning and examples show ML practices using both R and Python languages, the main languages inside Microsoft technologies.

What You'll Learn

• Choose the right Microsoft product for your machine learning solution
• Create and manage Microsoft's tool environments for development, testing, and production of a machine learning project
• Implement and deploy supervised and unsupervised learning in Microsoft products
• Set up Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, and HD Insight to perform machine learning
• Set up a data science virtual machine and test-drive installed tools, such as Azure ML Workbench, Azure ML Server Developer, Anaconda Python, Jupyter Notebook, Power BI Desktop, Cognitive Services, machine learning and data analytics tools, and more
• Architect a machine learning solution factoring in all aspects of self service, enterprise, deployment, and sharing

Who This Book Is For
Data scientists, data analysts, developers, architects, and managers who want to leverage machine learning in their products, organization, and services, and make educated, cost-saving decisions about their ML architecture and tool set.

了解如何使用微軟技術進行機器學習。本書教授如何使用微軟Power BI、Azure Data Lake、SQL Server、Stream Analytics、Azure Databricks、HD Insight等工具進行預測、描述和建議性分析。

分析大量實時數據並預測組織未來行為的能力對於長期成功至關重要。數據科學，尤其是機器學習（ML），是當今的改變遊戲規則者，應該成為每個公司戰略的重要組成部分。從業務理解、數據獲取和清理、建模以及在每個工具中部署機器學習過程的管理是一項有價值的技能。

《使用微軟技術進行機器學習》是一本以示範為主的書籍，解釋了如何使用微軟技術進行機器學習。您將獲得有關設計最佳架構以進行開發、共享和部署機器學習解決方案的寶貴見解。本書簡化了根據特定基礎設施需求和要求選擇適合機器學習的架構和工具的過程。

詳細內容介紹了監督和非監督機器學習的主要算法，並通過R和Python語言的示例展示了在微軟技術中使用機器學習的實踐。

您將學到什麼：

- 選擇適合您機器學習解決方案的微軟產品
- 創建和管理微軟的工具環境，用於開發、測試和生產機器學習項目
- 在微軟產品中實施和部署監督和非監督學習
- 設置Microsoft Power BI、Azure Data Lake、SQL Server、Stream Analytics、Azure Databricks和HD Insight以進行機器學習
- 設置數據科學虛擬機器並測試安裝的工具，例如Azure ML Workbench、Azure ML Server Developer、Anaconda Python、Jupyter Notebook、Power BI Desktop、Cognitive Services、機器學習和數據分析工具等
- 設計機器學習解決方案，考慮自助服務、企業、部署和共享的各個方面

本書適合對於在產品、組織和服務中利用機器學習並對於其機器學習架構和工具組做出明智、節省成本的決策的數據科學家、數據分析師、開發人員、架構師和經理閱讀。

Leila Etaati, PhD, is a Microsoft artificial intelligence and data platform MVP, speaker, trainer, and founding consultant with RADACAD where she trains and strategically advises some of today's largest global enterprises. Renowned in the field of AI and BI, she presents at many Microsoft events, including Ignite, Microsoft Data Insights Summit, PASS, and more. Leila is passionate about teaching others and resolving complex business solutions through the vast capabilities of machine learning and BI. She blogs and is author of Power BI and R through RADACAD.
 

Leila Etaati博士是微軟人工智慧和數據平台MVP、演講者、培訓師，也是RADACAD的創始顧問。她在AI和BI領域享有盛譽，在許多微軟活動中發表演講，包括Ignite、Microsoft Data Insights Summit、PASS等等。Leila熱衷於通過機器學習和BI的廣泛能力來教授他人並解決複雜的業務問題。她撰寫部落格並著有RADACAD的《Power BI and R》一書。