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    SpicyMags.xyz

    Recommendation Engine Bootcamp with 3 Capstone Projects

    Posted By: lucky_aut
    Recommendation Engine Bootcamp with 3 Capstone Projects

    Recommendation Engine Bootcamp with 3 Capstone Projects
    Duration: 4h 32m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 3.52 GB
    Genre: eLearning | Language: English

    Master recommendation systems Industry Projects using using modern recommendation techniques and methodologies

    What you'll learn:
    Learn about the different types of Recommender Systems
    Learn about Content based recommendation system
    Learn about Collaborative based filtering
    Learn about Singular Value Decomposition
    Learn recommending movies, books using the recommendation system
    Learn about Surprise Library for recommendation systems
    Learn how to use Correlation for Recommending similar Movies and Genres.
    Learn how to use different Techniques used for Imputing Missing Values.
    Quizzes and exercises
    Open Jobs Analyzer and Recommendation System

    Requirements:
    Good knowledge of Python programming
    Knowledge of Probability and Statistics concepts
    Knowledge of Machine Learning Algorithms
    A willingness to learn and practice.
    A positive attitude to success.
    Determination and Desire to Learn new things.

    Description:
    Welcome to the best online course on Recommendation Engine.
    Master various recommendation engines including Content based filtering, collaborative filtering, Singular value decomposition.
    Recommender systems aim to predict users' interests and recommend product items that quite likely are interesting for them.
    A recommendation engine is a type of data filtering tool using machine learning algorithms to recommend the most relevant items to a particular user or customer.
    It operates on the principle of finding patterns in consumer behavior data, which can be collected implicitly or explicitly.

    This course gives you a thorough understanding of the Recommendation systems.

    In this course, you will cover
    Use cases of recommender systems.
    Content-based filtering.
    Filtering movies based on genres.
    User-based collaborative filtering.
    Item-based collaborative filtering.
    Singular value decomposition using Surprise library.
    and much, much more!

    Not only this, you will also work on three very exciting projects.
    I am always available to answer your questions and help you along your data science journey. See you in class!
    You will learn to create a movie recommendation engine as well as a book recommendation engine and Open job analyzer system.
    It will be fun working on such exciting projects.
    You will see how easy it is to recommend new books or movies based on the user's past preferences.
    Instructor Support - Quick Instructor Support for any queries.
    I'm looking forward to see you in the course!

    I guarantee you will love this course.
    All the resources used in this course will be shared with you.

    Who this course is for:
    Data Analysts
    Data Scientists
    Job-seekers
    Anyone who wants to explore data science.
    Students and professionals who want to improve the training capabilities

    More Info