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Project: Linear Regression with NumPy and Python

Project: Linear Regression with NumPy and Python

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8.4/10 (Our Score)
Product is rated as #172 in category Machine Learning

Welcome to this project–based course on Linear Regression with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit–learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent and linear regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. This course runs on Coursera’s hands–on project platform called Rhyme. On Rhyme, you do projects in a hands–on manner in your browser. You will get instant access to pre–configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, NumPy, and Seaborn pre–installed.

Instructor Details

Snehan Kekre is a Machine Learning and Data Science Instructor at Rhyme. He will graduate in 2021 with a BSc in Computer Science and Artificial Intelligence from Minerva Schools at KGI, based in San Francisco. His interests include AI safety and alignment research. He believes that building a deep, technical understanding of machine learning and AI among students and engineers is necessary in order to grow the AI safety community. This passion drives him to design hands-on, project-based Machine Learning Courses on Rhyme.

Specification: Project: Linear Regression with NumPy and Python

Duration 2 hours
Year 2020
Level Beginner
Certificate Yes
Quizzes Yes

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    Lizardo R

    More programming background was necessary

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    Project: Linear Regression with NumPy and Python
    Project: Linear Regression with NumPy and Python

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