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Clustering Geolocation Data Intelligently in Python に戻る

Coursera Project Network による Clustering Geolocation Data Intelligently in Python の受講者のレビューおよびフィードバック

4.5
341件の評価
55件のレビュー

コースについて

In this 1.5-hour long project, you will learn how to clean and preprocess geolocation data for clustering. You will learn how to export this data into an interactive file that can be better understood for the data. You will learn how to cluster initially with a K-Means approach, before using a more complicated density-based algorithm, DBSCAN. We will discuss how to evaluate these models, and offer improvements to DBSCAN with the introduction of HDBSCAN. Note: 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....

人気のレビュー

NB

May 21, 2020

It would be better if there was no time limit to the project on VM as the VM was too slow.Rest the instructor was awesome ,content was perfect and whatever he taught was very well understood.

TS

Apr 18, 2020

Thanks a lot, It was a short, quick and very useful project learning experience. Hope you will provide more geospatial data analysis projects in future soon.

フィルター:

Clustering Geolocation Data Intelligently in Python: 1 - 25 / 54 レビュー

by Umar H

Apr 28, 2020

Course is amazing in terms of content, professor's instructions, and exercises. However, the tool used in this course is quite slow and actually messed up my most of time. I would advice students to use their own python notebooks on their computers for this exercise. I wish I knew it in advance so I might not have saved a lot of time.

by Mayank S

Apr 27, 2020

Great Project.

Learnt new applications of clustering algorithm.

Thanks sir.

by Pujith S K K

Apr 07, 2020

It is ok to try this as it is just for 2 hours and you will get hands-on experience working with Python libraries.

by Anisom C

Jun 07, 2020

This guided project is very much promising from each and every aspect. This project does not only provides a better understanding of Python, but it also provides an ample amount of knowledge of Data processing and Machine Learning.

by NEHA S B

May 21, 2020

It would be better if there was no time limit to the project on VM as the VM was too slow.Rest the instructor was awesome ,content was perfect and whatever he taught was very well understood.

by Tayyabali S

Apr 18, 2020

Thanks a lot, It was a short, quick and very useful project learning experience. Hope you will provide more geospatial data analysis projects in future soon.

by SOURAV D

Jun 13, 2020

Nice hands-on course to get introduced with the some popular clustering approaches like k-means, DBSCAN, HDBSCAN etc.

by ANKIT B S

Jun 17, 2020

It was really interesting. I was able to use this guidance in one of my college projects simultaneously. Thank you.

by Chaitanya S

Jun 25, 2020

The cloud Desktop Rhyme was slowing down. But the project content and instructor were superb.

by Ramya G R

Jun 08, 2020

I really enjoyed working with this project. Thank you so much for the valuable teaching.

by ACEBEDO, A M (

May 08, 2020

A most practical, hands-on approach to handling location intelligent data using Python!

by Abhishek P G

Jun 18, 2020

I am grateful to have the chance to participate in an online course like this!

by Sebastian J

Apr 23, 2020

Awesome course only for those who at least a base on clustering.

by Atharva M C

Apr 25, 2020

Excellent course for starting working with geolocation data.

by LATHA S K

Apr 30, 2020

Good project which is based on python and interesting.

by Carlos F d S A

Jul 04, 2020

Very good approaches ! Congratulations !

by Tejas

Jun 15, 2020

Nice hands on project experience

by Ashwin P

Apr 23, 2020

Excellent Course on Geolocation

by Prince R

Jun 07, 2020

Thank you for your hard work.

by Smriti T

May 22, 2020

good explanations !

by Gangone R

Jul 03, 2020

very useful course

by AISHWARYA V

Jun 04, 2020

good experience

by Vishal Y

Jun 03, 2020

Good project

by Deibid S R V

Jul 14, 2020

Excellent!

by Doss D

Jun 26, 2020

Thank you