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Comentários e feedback de alunos de Principal Component Analysis with NumPy da instituição Coursera Project Network

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Sobre o curso

Welcome to this 2 hour long project-based course on Principal Component Analysis 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 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 implement and apply PCA from scratch using NumPy in Python, conduct basic exploratory data analysis, and create simple data visualizations with Seaborn and Matplotlib. 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

TS

4 de out de 2020

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TA

30 de out de 2020

Good Introductory project to gain insights into PCA using Numpy and python.

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26 — 47 de 47 Avaliações para o Principal Component Analysis with NumPy

por Hari O U

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21 de jul de 2020

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13 de ago de 2020

por SASI V T

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por Abhishek P G

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24 de ago de 2020

por p s

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por Carlos C

14 de dez de 2020

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1 de jun de 2020

por Alok a

5 de ago de 2020

por Sumit S

31 de mai de 2020

por Ashutosh S T

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por GUNDA N

10 de mai de 2020

por Baviskar Y S

2 de out de 2020

por Jorge G

25 de fev de 2021

por Mohinder S

3 de jun de 2020

por Задойный А

24 de jul de 2020