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    Détails du Torrent Pour "Udemy - Complete Guide to Data Science Applications with Streamlit"

    Udemy - Complete Guide to Data Science Applications with Streamlit

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    Dernière vérification: 13-06-2021 01:44:36

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    Details
    _NAME_:Udemy - Complete Guide to Data Science Applications with Streamlit
    Description:

    Description

    Analyzing data and building machine learning models is one thing. Packaging these analyses and models such that they are sharable is a different ball game altogether.

    This course aims at teaching you the fastest and easiest way to build and share data applications using Streamlit. You don’t need any experience in building front-end applications for this. Here are some of the things you can expect to cover in this course:

       Python Crash Course
       NumPy Crash Course
       Introduction to Streamlit
       Integrating Matplotlit and Seaborn in Streamlit
       Using Altair and Vega-Lite in Streamlit
       Understand all Streamlit Widgets
       Upload and Process Files
       Build an Image Processing Application
       Develop a Natural Language Processing Application
       Integrate Maps with Streamlit
       Implement Plotly Graphs
       Authenticate Your Applications
       Laying Out your Application in Streamlit
       Developing with Streamlit Components
       Deploying Data Applications

    At the end of the course, you will have built several applications that you can include in your data science portfolio. You will also have a new skill to add to your resume.

    The course also comes with a 30-day money-back guarantee. Enroll now and if you don’t like it you will get your money back no questions asked.
    Who this course is for:

       Individuals interested in building data science and machine learning applications in Python

    Requirements

       Basic Python Programming, however a Python crash course is included

    Last Updated 12/2020
    YouTube Video:
    Catégorie:Tutorials
    Langue :English  English
    Taille totale:4.33 GB
    Info Hash:8F0B5E1F3F1F0800A003F8E2B87F98780B5AC026
    Ajouté par:tutsnode Verified UploaderVIP
    Date:2021-01-08 00:07:22
    Statut Torrent:Torrent Verified


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