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学生对 Coursera Project Network 提供的 Principal Component Analysis with NumPy 的评价和反馈

4.7
148 个评分
26 条评论

课程概述

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 - Principal Component Analysis with NumPy 的 25 个评论(共 26 个)

创建者 Rishit C

Jun 01, 2020

Some places the code used could have been simplified to be easier for the learner to understand. For example: (eigen_vectors.T[:][:])[:2].T was used in the course video but it can be replaced by eigen_vectors[:, :2]. The second one which I used is much simpler and cleaner to understand.

Thank You.

创建者 Pranav D

Jun 19, 2020

Did not focus on the mathematics part of PCA. The explanation could have been better and easy to understand.

创建者 Zixiang M

Jun 12, 2020

The platform is really hard to use, the screen is small, and there're lags when I'm typing into the jupyter notebook on the virtual desktop.

创建者 Mayank S

Apr 25, 2020

Learned Applying PCA

Concise course.

Liked the method of teaching.

创建者 Dr.T.Hemalatha c

Jun 09, 2020

simple and an elegant example to understand

创建者 Jayasanthi

Apr 25, 2020

Very good explanation with demo. Thank you.

创建者 Dr. C S G

Jun 09, 2020

This course is very useful in learning PCA

创建者 PATIL P R

May 12, 2020

Nice and Helpful course...Thanks to Team

创建者 Dr. P W

May 31, 2020

This is good course for beginners

创建者 Sitesh R

Jun 28, 2020

The couse was made very simple.

创建者 ENRICA M M

May 27, 2020

Corso davvero utile e semplice.

创建者 Oscar A C B

Jun 12, 2020

Just as simple as I needed!

创建者 Gangone R

Jul 03, 2020

very useful course

创建者 Kamol D D

Apr 18, 2020

Very Satisfactory

创建者 Hari O U

Apr 19, 2020

Great experience

创建者 Abhishek P G

Jun 15, 2020

satisfied

创建者 p s

Jun 29, 2020

Good

创建者 tale p

Jun 28, 2020

good

创建者 Vajinepalli s s

Jun 16, 2020

nice

创建者 Vipul P

Jun 14, 2020

The course felt a bit too short and the time allotted for the guided project was barely enough to complete it in time leaving little to no room for thinking and rewinding the videos which made it a bit uncomfortable to take.

创建者 Prashant P

Jun 01, 2020

Course is amazing, got many concepts clear, learned a lot. Would also be great if more than one datasets are taken as excercise.

创建者 Sumit S

Jun 01, 2020

It was quite conceptional but the instructor made it easy for me to implement and follow along.

创建者 Ashutosh S T

May 09, 2020

Excellence experiece, good content for begineers, thanx coursera.

创建者 GUNDA N

May 10, 2020

The instructor was good with explanation .