Torrent details for "Wolf M. Mathematical Foundations of Supervised Learning 2023" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
20.8 MB
Info Hash:
F966CB14B5903B7CF0F1404F79299BB519C71269
Added By:
Added:
Aug. 10, 2025, 11:54 a.m.
Stats:
|
(Last updated: Aug. 10, 2025, 11:57 a.m.)
| File | Size |
|---|---|
| Wolf M. Mathematical Foundations of Supervised Learning 2023.pdf | 4.1 MB |
| Wolf A. The Machine Learning Simplified. A Gentle Introduction...2022.pdf | 16.7 MB |
Name
DL
Uploader
Size
S/L
Added
-
11.9 MB
[13
/
3]
2023-11-29
| Uploaded by indexFroggy | Size 11.9 MB | Health [ 13 /3 ] | Added 2023-11-29 |
-
20.8 MB
[59
/
13]
2025-08-10
| Uploaded by andryold1 | Size 20.8 MB | Health [ 59 /13 ] | Added 2025-08-10 |
-
7.4 GB
[115
/
12]
2025-04-06
| Uploaded by eXpOrTeRICV | Size 7.4 GB | Health [ 115 /12 ] | Added 2025-04-06 |
NOTE
SOURCE: Wolf M. Mathematical Foundations of Supervised Learning 2023
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format What is machine learning? Machine learning is often considered part of the field of artificial intelligence, which in turn may largely be regarded as a subfield of computer science. The aim of achine learning is to exploit optimization techniques and, in most cases, vast amounts of data in order to devise complex models or algorithms in an automated way. Loosely speaking, it is about roducing computer programs without writing them. Instead, one sets up an optimization procedure, which in this context is often called ‘learning’ or ‘training’, that eventually leads to the sought omputer program. Machine learning techniques are typically used whenever large amounts of data are available and when one aims at a computer program that is (too) difficult to program ‘directly’. Standard examples are programs that recognize faces, handwriting, or speech, drive cars, recommend products, translate texts or play Go. These are hard to program from scratch so one uses machine learning algorithms that produce such programs from large amounts of data. Introduction. Learning Theory. Neural networks. Kernel methods. Probability theory
×