Udemy - Real World Data Science Case Studies, Projects Using Python

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 1.9 GB
  • Uploaded By tutsnode
  • Downloads 155
  • Last checked Nov. 24th '20
  • Date uploaded Nov. 22nd '20
  • Seeders 15
  • Leechers 21

Infohash : F6BD2553D744350E3F3021252E8C54011143CAF5


Data Science is not like any other technology, but it is in many cases the only technology that can solve certain problems. We need to ensure that all people involved in the project have a common understanding of what is required, how the process works, and that we have a realistic view of what is possible with the tools at hand. To boil down all this to its core components we could consider a few important rules:

create a common ground of understanding, this will ensure the right mindset
state early how progress should be measured
communicate clearly how different machine learning concepts works
acknowledge and consider the inherited uncertainty, it is part of the process

In this course, we are going to work on the following projects

Bangalore House Price Prediction Using Machine Learning.
Zomato Restaurant Data Analysis
Indian Liver Patient Data Analysis
Predicting The Income Level Based On U.S Census Data.

Who this course is for:

Beginners in machine learning


Knowledge Of Machine Learning
Knowledge Of Python

Last Updated 11/2020


Real World Data Science Case Studies, Projects Using Python
  • Real World Data Science Case Studies, Projects Using Python.zip (1.9 GB)
  • [TGx]Downloaded from torrentgalaxy.to .txt (0.6 KB)
  • TutsNode.com.txt (0.1 KB)


  • udp://inferno.demonoid.pw:3391/announce
  • udp://tracker.openbittorrent.com:80/announce
  • udp://tracker.opentrackr.org:1337/announce
  • udp://torrent.gresille.org:80/announce
  • udp://glotorrents.pw:6969/announce
  • udp://tracker.leechers-paradise.org:6969/announce
  • udp://tracker.pirateparty.gr:6969/announce
  • udp://tracker.coppersurfer.tk:6969/announce
  • udp://ipv4.tracker.harry.lu:80/announce
  • udp://9.rarbg.to:2710/announce
  • udp://shadowshq.yi.org:6969/announce
  • udp://tracker.zer0day.to:1337/announce