|
|
|
|
| LEADER |
02411nmm a2200421 u 4500 |
| 001 |
EB001908174 |
| 003 |
EBX01000000000000001071076 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
210123 ||| eng |
| 050 |
|
4 |
|a HG4515.5
|
| 100 |
1 |
|
|a Konczyk, Jakub
|
| 245 |
0 |
0 |
|a AI for finance
|c Jakub Konczyk
|
| 246 |
3 |
1 |
|a Artificial Intelligence for finance
|
| 260 |
|
|
|a [Place of publication not identified]
|b Packt Publishing
|c 2019
|
| 300 |
|
|
|a 1 streaming video file (2 hr., 19 min., 25 sec.)
|
| 653 |
|
|
|a Finance / Data processing / http://id.loc.gov/authorities/subjects/sh2020000036
|
| 653 |
|
|
|a Machine learning / http://id.loc.gov/authorities/subjects/sh85079324
|
| 653 |
|
|
|a Finances / Informatique
|
| 653 |
|
|
|a Artificial intelligence / http://id.loc.gov/authorities/subjects/sh85008180
|
| 653 |
|
|
|a Artificial Intelligence
|
| 653 |
|
|
|a Finance / Data processing / fast / (OCoLC)fst00924370
|
| 653 |
|
|
|a Intelligence artificielle
|
| 653 |
|
|
|a Apprentissage automatique
|
| 653 |
|
|
|a Artificial intelligence / fast / (OCoLC)fst00817247
|
| 653 |
|
|
|a Finance / Decision making / Data processing
|
| 653 |
|
|
|a artificial intelligence / aat
|
| 653 |
|
|
|a Finance / Decision making / Data processing / fast / (OCoLC)fst00924373
|
| 653 |
|
|
|a Finances / Prise de décision / Informatique
|
| 653 |
|
|
|a Machine learning / fast / (OCoLC)fst01004795
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 500 |
|
|
|a Title from resource description page (Safari, viewed April 10, 2019)
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/videos/~/9781789803778/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 153.83
|
| 082 |
0 |
|
|a 000
|
| 082 |
0 |
|
|a 332
|
| 520 |
|
|
|a "In this course, you'll first learn how to quickly get started with ML in finances by predicting the future currency exchange rates using a simple modern machine learning method. In this example, you'll learn how to choose the basic data preparation method and model and then how to improve them. In the next module, you'll discover a variety of ways to prepare data and then see how they influence models training accuracy. In the last module, you'll learn how to find and test a few key modern machine learning models to pick up the best performing one. After finishing this course, you'll have a solid introduction to apply ML methods to financial data forecasting."--Resource description page
|