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Вернуться к Principal Component Analysis with NumPy

Отзывы учащихся о курсе Principal Component Analysis with NumPy от партнера Coursera Project Network

Оценки: 228
Рецензии: 39

О курсе

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....

Лучшие рецензии


Sep 09, 2020

This is a great project. The instructor facilitates clear and practically.


Apr 25, 2020

Learned Applying PCA\n\nConcise course.\n\nLiked the method of teaching.

Фильтр по:

26–39 из 39 отзывов о курсе Principal Component Analysis with NumPy

автор: Kamlesh C

Jul 08, 2020


автор: Raja R G K

Aug 24, 2020


автор: p s

Jun 29, 2020


автор: tale p

Jun 28, 2020


автор: Vajinepalli s s

Jun 16, 2020


автор: 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.

автор: 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.

автор: Alok a

Aug 05, 2020

It's a good course for someone to try out his knowledge of the basic packages and the concepts and the maths behind PCA.

автор: Sumit S

Jun 01, 2020

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

автор: Ashutosh S T

May 09, 2020

Excellence experiece, good content for begineers, thanx coursera.

автор: GUNDA N

May 10, 2020

The instructor was good with explanation .

автор: Mohinder

Jun 03, 2020

Well, this project seems to be very basic and can be created using WEBSITE LIKE:

автор: Задойный А

Jul 24, 2020

Очень слабые объяснения. Всё как "магия".