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Volver a Classification Trees in Python, From Start To Finish

Opiniones y comentarios de aprendices correspondientes a Classification Trees in Python, From Start To Finish por parte de Coursera Project Network

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219 calificaciones
45 reseña

Acerca del Curso

In this 1-hour long project-based course, you will learn how to build Classification Trees in Python, using a real world dataset that has missing data and categorical data that must be transformed with One-Hot Encoding. We then use Cost Complexity Pruning and Cross Validation to build a tree that is not overfit to the Training Dataset. 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 (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with Python and the theory behind Decision Trees, Cost Complexity Pruning, Cross Validation and Confusion Matrices. Notes: - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Principales reseñas

RR
17 de ago. de 2020

Josh Starmer's videos and courses are always simple and easy to understand. Thank you for this wonderful course. I will definitely recommend everyone to take this course.

SS
17 de jun. de 2020

A very informative and well guided short session to understand overview of Classification Trees. Covers lot of important concepts in 1 hour. Highly recommend

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1 - 25 de 44 revisiones para Classification Trees in Python, From Start To Finish

por Erick M F d S

15 de may. de 2020

Short, but good content. Still lots of problems with the Rhyme platform.

The main problem with the guided project was that the Rhyme platform is still problematic: the video playback was constantly being interrupted for buffering, especially at higher playback speeds (my internet connection is good enough for 4k streaming), the cloud desktop for the Jupyter notebook is quite laggy, doesn't allow copy and paste between cloud and own computer; the whole UX of a single browser window for both video and remote desktop is very awkward and inflexible; the video playback was paused every time the browser window was out of focus, as when I was writing some notes on another window. Finally, I couldn't easily download the completed code, for use in my own projects, thus reducing my capacity to reuse what was learned without extensive notes.

Guided projects are a great idea. Not sure I would pay U$ 10 for simple projects when there are similar excellent code freely available on Kaggle or github, but Coursera's selection of content might make it worth. But the current performance of Rhyme is still insufficient for a paid service. I can get better service out of Google Colab, for free!

por Joseph j D

16 de abr. de 2020

new to learn.useful

por Киселева К К

22 de nov. de 2021

After the first 5 seconds I've felt something was wrong and missing. And suddenly I realized what it was. "Hello, and welcome to STAT QUEST!" I am a huge fan of the lecturer's Youtube channel, he is the best statistics lecturer I've ever heard. Was not disappointed by this practical project. His explanations are always like "ba-am, that's so easy"

por Maria B

14 de jun. de 2020

I love Josh Starmer's teaching style. He's definitely one of the best teachers I know. I will always recommend his work. However, I would have enjoyed the course a little more if he had expanded his window in the Rhyme platform, the size of the screen makes it hard to follow sometimes.

por Rahul R

18 de ago. de 2020

Josh Starmer's videos and courses are always simple and easy to understand. Thank you for this wonderful course. I will definitely recommend everyone to take this course.

por Sagar S

18 de jun. de 2020

A very informative and well guided short session to understand overview of Classification Trees. Covers lot of important concepts in 1 hour. Highly recommend

por Yasir A

14 de sep. de 2020

Awesome Instructor! Like this course. It clears basic knowledge about DecisionTreeClassifier, Tree Pruning, Dealing with missing Data etc.

por Karna D

25 de ago. de 2020

This is a great course. The instructor does a wonderful job of explaining concepts and providing useful code.

por Alvaro V

26 de jul. de 2020

Very good and clear project, ideal to imporve knowledge in supervised learning and decision trees.

por KALPANA

10 de may. de 2020

Machine learning algorithms used for data-set classification and many more works really impressed.

por Anand S

28 de jun. de 2020

Liked, easy to understand and utilize the knowledge in a similar dataset.

por Mayank S

2 de may. de 2020

Good Course. Cost Complexity Pruning explained nicely. Bammmm!!!!!!!!

por ZAINAB S I H A

22 de jun. de 2020

الشاشة جدا صغير اضطر اعمل تدريبيا على كمبيوتر اخر حتى استطيع التركيز

por Punam P

16 de may. de 2020

Nice and Helpful course for Begineers..Thanks to Team

por IMRAN H I

28 de ago. de 2020

Good platform to learn about this type of project.

por coding s

14 de dic. de 2020

All the code and concepts were clearly explained.

por Szymon K

18 de jul. de 2020

Nice basics of scikit-learn DecisionTrees

por Sagar P

30 de jun. de 2020

Good course to learn classification Tree

por Carlos A P

25 de oct. de 2020

Good intro to Classification problems

por Kodhai.E

22 de may. de 2020

Best Hand-on training by course

por SUGUNA M

23 de nov. de 2020

Good project based course

por Rati K J

8 de jun. de 2020

IT WAS BETTER EXPERIENCE

por Gangone R

2 de jul. de 2020

very useful course

por Nikita D S

25 de abr. de 2020

Its very useful...

por Akshit B

1 de sep. de 2020

Just excellent.