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Voltar para Logistic Regression with Python and Numpy

Comentários e feedback de alunos de Logistic Regression with Python and Numpy da instituição Coursera Project Network

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Sobre o curso

Welcome to this project-based course on Logistic 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, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. By the time you complete this project, you will be able to build a logistic regression model using Python and NumPy, conduct basic exploratory data analysis, and implement gradient descent from scratch. The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory. 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....

Melhores avaliações

DP

8 de abr de 2020

Want to do a project in Logistic Regression. You are at the right spot Don't delay and take the course.

MT

9 de mar de 2020

Easy to follow along, each step was made very clear, and I understood the justification behind steps.

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1 — 24 de 24 Avaliações para o Logistic Regression with Python and Numpy

por Shiva S T

9 de mar de 2020

por Haofei M

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por Megan T

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por Ashwin K

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por Saikat K

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por p s

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por ANURAG P

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por Munna K

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por Chow K M

4 de out de 2021

por Manzil-e A K

20 de jul de 2020

por Rosario P

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por Abdul Q

30 de abr de 2020

por Weerachai Y

8 de jul de 2020

por Александр П

9 de mar de 2020