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Voltar para Principal Component Analysis with NumPy

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

65 classificações
8 avaliações

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....
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1 — 8 de {totalReviews} Avaliações para o Principal Component Analysis with NumPy

por Mayank S

Apr 25, 2020

Learned Applying PCA

Concise course.

Liked the method of teaching.

por Jayasanthi

Apr 25, 2020

Very good explanation with demo. Thank you.


May 12, 2020

Nice and Helpful course...Thanks to Team


May 27, 2020

Corso davvero utile e semplice.

por Kamol D D

Apr 18, 2020

Very Satisfactory

por Hari O U

Apr 19, 2020

Great experience

por Ashutosh S T

May 09, 2020

Excellence experiece, good content for begineers, thanx coursera.


May 10, 2020

The instructor was good with explanation .