Kernel Methods for Machine Learning with Math and Python - 100 Ex...

  • Category Other
  • Type E-Books
  • Language English
  • Total size 2.3 MB
  • Uploaded By freecoursewb
  • Downloads 160
  • Last checked 1 year ago
  • Date uploaded 1 year ago
  • Seeders 9
  • Leechers 0

Infohash : 85FA4EB3291430F14CF051991ED8E42403672B1B

Warning! Use a V𝙿N When Downloading Torrents!
Your IP Address is . Location
Your Internet Provider can see when you download torrents! Hide your IP Address with a V𝙿N
1337x recommends using Trust.Zone V𝙿N to hide your torrenting. It's FREE HIDE ME NOW


Kernel Methods for Machine Learning with Math and Python: 100 Exercises for Building Logic



https://DevCourseWeb.com

English | 2022 | ISBN: 9811904006 | 220 Pages | PDF | 2 MB

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than relying on knowledge or experience. This textbook addresses the fundamentals of kernel methods for machine learning by considering relevant math problems and building Python programs.

The book’s main features are as follows

Files:

[ DevCourseWeb.com ] Kernel Methods for Machine Learning with Math and Python - 100 Exercises for Building Logic
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here !
    • Bonus Resources.txt (0.4 KB)
    • KernelMethodsforMachineLearningwithMathandPytho.pdf (2.3 MB)

There are currently no comments. Feel free to leave one :)

Code:

  • udp://tracker.torrent.eu.org:451/announce
  • udp://tracker.tiny-vps.com:6969/announce
  • http://tracker.foreverpirates.co:80/announce
  • udp://tracker.cyberia.is:6969/announce
  • udp://exodus.desync.com:6969/announce
  • udp://explodie.org:6969/announce
  • udp://tracker.opentrackr.org:1337/announce
  • udp://9.rarbg.to:2780/announce
  • udp://tracker.internetwarriors.net:1337/announce
  • udp://ipv4.tracker.harry.lu:80/announce
  • udp://open.stealth.si:80/announce
  • udp://9.rarbg.to:2900/announce
  • udp://9.rarbg.me:2720/announce
  • udp://opentor.org:2710/announce