|
|
|
|
| LEADER |
02349nmm a2200325 u 4500 |
| 001 |
EB001922512 |
| 003 |
EBX01000000000000001085414 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
210123 ||| eng |
| 020 |
|
|
|a 9781491978757
|
| 050 |
|
4 |
|a Q325.5
|
| 100 |
1 |
|
|a Géron, Aurélien
|
| 245 |
0 |
0 |
|a Getting started with TensorFlow
|c Aurélien Géron
|
| 260 |
|
|
|a [Place of publication not identified]
|b O'Reilly
|c 2017
|
| 300 |
|
|
|a 1 volume
|b illustrations
|
| 653 |
|
|
|a Machine learning / http://id.loc.gov/authorities/subjects/sh85079324
|
| 653 |
|
|
|a Artificial intelligence / fast
|
| 653 |
|
|
|a Artificial intelligence / http://id.loc.gov/authorities/subjects/sh85008180
|
| 653 |
|
|
|a Intelligence artificielle
|
| 653 |
|
|
|a Machine learning / fast
|
| 653 |
|
|
|a Apprentissage automatique
|
| 653 |
|
|
|a artificial intelligence / aat
|
| 740 |
0 |
2 |
|a Hands-on machine learning with Scikit-Learn and TensorFlow
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b OREILLY
|a O'Reilly
|
| 500 |
|
|
|a "From Hands-on machine learning with Scikit-Learn and TensorFlow by Aurélien Géron"--Cover. - Date of publication from resource description page
|
| 856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9781491978757/?ar
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 000
|
| 520 |
|
|
|a This Lesson will answer your key questions about getting started with TensorFlow, a library for machine learning and working with deep neural networks. What you'll learn--and how you can apply it You'll learn the necessary basics to get starting using TensorFlow and will be able to follow TensorFlow tutorials. This lesson is for you because You've gained a technical understanding of TensorFlow basics and are ready to move to the next step of training a very large neural network. You want to learn the basics of TensorFlow, including installation, managing graphs, placeholders, and optimization. You have some programming experience and you eventually want to take your skills to the next level and train very large neural nets. You don't have much experience in deep learning libraries, hands-on with examples of code. Prerequisites: Understanding of gradient descent Programming experience (understanding of how to code in Python) Materials or downloads needed: Python TensorFlow (recommend latest version, code written and tested on v. 0.11)
|