Team OS : Your Only Destination To Custom OS !!

Welcome to TeamOS Community, Register or Login to the Community to Download Torrents, Get Access to Shoutbox, Post Replies, Use Search Engine and many more features. Register Today!

Torrent + Direct Data Mining with Python: Theory, Application, and Case Studies

Ronaldo99

Uploader
Power User
✅ Verified Member
Downloaded
135.2 GB
Uploaded
13.1 TB
Ratio
99.41
Seedbonus
333,725
Upload Count
286 (321)
Member for 9 years
Data Mining with Python:
Theory, Application, and Case Studies
QXvTg9.jpeg

English | 2024 | ISBN: 1032598905
415 pages | True PDF | 13.77 MB



Data is everywhere and it’s growing at an unprecedented rate.
But making sense of all that data is a challenge.
Data Mining is the process of discovering patterns and knowledge from large data sets,
and Data Mining with Python focuses on the hands-on approach to learning Data Mining.

It showcases how to use Python Packages to fulfill the Data Mining pipeline,
which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.


The contents are organized based on the Data Mining pipeline,
so readers can naturally progress step by step through the process.


Topics, methods, and tools are explained in three aspects:
“What it is” as a theoretical background, “why we need it” as an application orientation,
and “how we do it” as a case study.


This book is designed to give students, data scientists,
and business analysts an understanding of Data Mining concepts in an applicable way.


Through interactive tutorials that can be run, modified,
and used for a more comprehensive learning experience,

this book will help its readers to gain practical skills
to implement Data Mining techniques in their work.



QXvdmt.jpeg

QXv0S8.jpeg

QXvGxJ.jpeg

QXvMMD.jpeg

QXvYNg.jpeg

QXviP5.jpeg

QXvchm.jpeg

QXvLlA.jpeg

QXvmIR.jpeg

QXvVge.jpeg

QXvw6U.jpeg

Download
 
  • Created With:
    Tixati v3.24
    Comment:
    Downloaded From https://www.teamos.xyz/
    Peers:
    14 Seeders + 0 Leechers = 14 Peers
    Last Announced
    Info Hash:
    74830bf3a59bf0bc8dd958f75aa76d1f60d7bb13
  • Loading…

mimi2016

Member
Downloaded
74.3 GB
Uploaded
262.4 GB
Ratio
3.53
Seedbonus
2,788
Upload Count
0 (0)
Member for 8 years
Thank you sharing this good learning material.
 
Top