This page requires that JavaScript be enabled in your browser.
Learn how »
Machine Learning: Current and Future
Etienne Bernard
As part of the Wolfram Language, we developed efficient yet user-friendly machine learning tools aimed for use at both beginners and experts in the field. These tools include a neural network framework, a repository of pretrained networks and fully automated machine learning functions. In this talk, Etienne Bernard gives an overview of these tools, presents the novelties since Version 12 and discusses our current and future projects in this area.
Thanks for your feedback.
Channels: Technology Conference
1311 videos match your search.
|
Jay Weininger |
|
Dennis Collins |
|
Maureen Baehr, Benji Bernstein & Ben Kickert |
|
Галина Михалкина, Григорий Фридман |
|
Тигран Ишханян |
|
Микаэл Эгибян |
|
Ankit Naik |
|
Микаэл Эгибян |
|
Галина Михалкина |
|
Антон Екименко, Кирилл Белов |
|
Роман Аверьянов |
|
Алексей Семенов |
|
Мария Гундина |
|
Николай Сосновский |
|
Николай Вавилов |
|
Александр Ганьшин |
|
Виктория Карабанова, Илья Марчевский |
|
Олег Кофнов |
|
Галина Михалкина |
|
Roman Maeder A look at the fascinating toppling sequences that arise from various initial conditions, leading to fractal images, and discuss efficient code for generating animations and images with millions of grains ... |