Tags
Language
Tags
June 2025
Su Mo Tu We Th Fr Sa
1 2 3 4 5 6 7
8 9 10 11 12 13 14
15 16 17 18 19 20 21
22 23 24 25 26 27 28
29 30 1 2 3 4 5
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

    Data Science with SQL Server Quick Start Guide : Integrate SQL Server with Data Science

    Posted By: readerXXI
    Data Science with SQL Server Quick Start Guide : Integrate SQL Server with Data Science

    Data Science with SQL Server Quick Start Guide :
    Integrate SQL Server with Data Science

    by Dejan Sarka
    English | 2018 | ISBN: 1789537126 | 196 Pages | PDF | 7.9 MB

    SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you.

    This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment.

    You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm.

    What you will learn:

    Use the popular programming languages,T-SQL, R, and Python, for data science
    Understand your data with queries and introductory statistics
    Create and enhance the datasets for ML
    Visualize and analyze data using basic and advanced graphs
    Explore ML using unsupervised and supervised models
    Deploy models in SQL Server and perform predictions

    SQL Server professionals who want to start with data science, and data scientists who would like to start using SQL Server in their projects will find this book to be useful. Prior exposure to SQL Server will be helpful.