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biskampling

biskampling

著者: ardiles kowe
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WELCOME To My Podcast!! Hosted by Ausha. See ausha.co/privacy-policy for more information.ardiles kowe
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  • >Read Understanding Construction Drawings – Mark W. Huth
    2024/12/04

    Read Ebooks Understanding Construction Drawings Here https://myideasee.blogspot.com/?book=1337408638

    Synopsis : Array

    Reading Understanding Construction Drawings

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  • >Read IBEW Aptitude Test Prep 2024-2025: LATEST IBEW Exam Prep for the IBEW Apprenticeship Aptitude Test Prep 2024. Featuring Detailed IB...
    2024/12/04

    Read Ebooks IBEW Aptitude Test Prep 2024-2025: LATEST IBEW Exam Prep for the IBEW Apprenticeship Aptitude Test Prep 2024. Featuring Detailed IBEW Study Guide Review Material and 539 IBEW Practice Questions Here https://myideasee.blogspot.com/?book=1964079926

    Synopsis : Array

    Reading IBEW Aptitude Test Prep 2024-2025: LATEST IBEW Exam Prep for the IBEW Apprenticeship Aptitude Test Prep 2024. Featuring Detailed IBEW Study Guide Review Material and 539 IBEW Practice Questions

    Download IBEW Aptitude Test Prep 2024-2025: LATEST IBEW Exam Prep for the IBEW Apprenticeship Aptitude Test Prep 2024. Featuring Detailed IBEW Study Guide Review Material and 539 IBEW Practice Questions

    PDF/EBooks IBEW Aptitude Test Prep 2024-2025: LATEST IBEW Exam Prep for the IBEW Apprenticeship Aptitude Test Prep 2024. Featuring Detailed IBEW Study Guide Review Material and 539 IBEW Practice Questions

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  • >Read Machine Learning Pocket Reference: Working with Structured Data in Python – Matt Harrison
    2024/12/04

    Read Ebooks Machine Learning Pocket Reference: Working with Structured Data in Python Here https://myideasee.blogspot.com/?book=1492047546

    Synopsis : With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project.

    Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics.

    This pocket reference includes sections that cover:

    Classification, using the Titanic dataset
    Cleaning data and dealing with missing data
    Exploratory data analysis
    Common preprocessing steps using sample data
    Selecting features useful to the model
    Model selection
    Metrics and classification evaluation
    Regression examples using k-nearest neighbor, decision trees, boosting, and more
    Metrics for regression evaluation
    Clustering
    Dimensionality reduction
    Scikit-learn pipelines

    Reading Machine Learning Pocket Reference: Working with Structured Data in Python

    Download Machine Learning Pocket Reference: Working with Structured Data in Python

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