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  • E

    Topic
    2 Concepts | 15 Assessments | 701 Learners

    This is an end-to-end Machine Learning project. You would start by learning how to load a dataset, visualize it, fill in the missing values, create pipelines, handle categorical variables, train models based on that data, and finally predict using that model.

    This will not only help you understand how to train a machine learning model, but will also give you a detailed idea of how to clean and prepare data for machine learning, train the model, and fine tune it in real life projects.

    Skills you will develop:

    1. scikit-learn
    2. Data visualization
    3. Treating missing values in dataset 4 …
    Instructor: Cloudxlab
  • E

    Topic
    48 Concepts | 23 Questions | 24 Assessments | 367 Learners

    This is a beginner-friendly end-to-end project for Machine Learning. The only prerequisite of the project is to know Python. Other than it, everything is covered in the project itself.

    Perks of this project

    • This project is prepared while keeping beginners in mind. It will walk you through all the steps included in a Machine Learning Pipeline in detail.
    • You will learn the answers to the three most important questions, i.e., Why, When, and How to do a particular thing.
    • The concepts used in performing a step are explained there and then in a simple way for beginners.
    • This project …
    Instructor: Shubh Tripathi