Cargando…
Reinforcement learning in motion /
"Reinforcement Learning in Motion introduces you to the exciting world of machine systems that learn from their environments! Developer, data scientist, and expert instructor Phil Tabor guides you from the basics all the way to programming your own constantly-learning AI agents. In this course,...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Manning Publications,
2019.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cgm a2200000 i 4500 | ||
|---|---|---|---|
| 001 | OR_on1090069403 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o c | ||
| 007 | cr cna|||||||| | ||
| 007 | vz czazuu | ||
| 008 | 190318s2019 xx 357 o vleng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d OCLCF |d TOH |d OCLCO |d OCLCQ |d OCLCO | ||
| 029 | 1 | |a AU@ |b 000067116951 | |
| 035 | |a (OCoLC)1090069403 | ||
| 037 | |a CL0501000034 |b Safari Books Online | ||
| 050 | 4 | |a Q325.6 | |
| 049 | |a UAMI | ||
| 100 | 1 | |a Tabor, Phil, |e speaker. | |
| 245 | 1 | 0 | |a Reinforcement learning in motion / |c Phil Tabor. |
| 264 | 1 | |a [Place of publication not identified] : |b Manning Publications, |c 2019. | |
| 300 | |a 1 online resource (1 streaming video file (5 hr., 56 min., 42 sec.)) | ||
| 336 | |a two-dimensional moving image |b tdi |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 337 | |a video |b v |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 511 | 0 | |a Presenter, Phil Tabor. | |
| 500 | |a Title from resource description page (Safari, viewed March 13, 2019). | ||
| 520 | |a "Reinforcement Learning in Motion introduces you to the exciting world of machine systems that learn from their environments! Developer, data scientist, and expert instructor Phil Tabor guides you from the basics all the way to programming your own constantly-learning AI agents. In this course, he'll break down key concepts like how RL systems learn, how to sense and process environmental data, and how to build and train AI agents. As you learn, you'll master the core algorithms and get to grips with tools like Open AI Gym, numpy, and Matplotlib. Reinforcement systems learn by doing, and so will you in this hands-on course! You'll build and train a variety of algorithms as you go, each with a specific purpose in mind. The rich and interesting examples include simulations that train a robot to escape a maze, help a mountain car get up a steep hill, and balance a pole on a sliding cart. You'll even teach your agents how to navigate Windy Gridworld, a standard exercise for finding the optimal path even with special conditions!"--Resource description page | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Reinforcement learning. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 6 | |a Apprentissage par renforcement (Intelligence artificielle) | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Artificial intelligence. |2 fast |0 (OCoLC)fst00817247 | |
| 650 | 7 | |a Machine learning. |2 fast |0 (OCoLC)fst01004795 | |
| 650 | 7 | |a Reinforcement learning. |2 fast |0 (OCoLC)fst01732553 | |
| 655 | 4 | |a Electronic videos. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/videos/~/10000MNLV201807/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 994 | |a 92 |b IZTAP | ||