Deep Learning Using SAS Software
This course introduces the pivotal components of deep learning. You learn how to build deep feedforward, convolutional, recurrent networks, and variants of denoising autoencoders. The neural networks are used to solve problems that include traditional classification, image classification, and sequence-dependent outcomes. The course contains a healthy mix of theory and application. Hands-on demonstration and practice problems are included to reinforce key concepts. Hyperparameter search methods are described and demonstrated to find an optimal set of deep learning models. Transfer learning is covered in detail because of the emergence of this field has shown promise in deep learning. Lastly, you learn how to customize a SAS deep learning model to research new areas of deep learning.În urma acestui curs, veți învăța să
Cine ar trebui să participe la cursMachine learners and those interested in deep learning, computer vision, or natural language processing
Before attending this course, you should have at least an introductory-level familiarity with basic neural network modeling ideas. You can gain this neural network modeling knowledge by completing either the Neural Networks: Essentials or Neural Network Modeling course. Previous SAS software experience is helpful but not required.
Acest curs este despre SAS Viya, SAS Visual Data Mining and Machine Learning software.
Introduction to Deep Learning
|Titlul||Durata||Perioada de acces||Limba||Preț (fără TVA)||Adaugă în coș|
|Deep Learning Using SAS Software||14.0 ore||180 zile||English||671 EUR|
|Data||Locație||Orar||Limba||Preț (fără TVA)||Adaugă în coș|
|09-10 MAR 2020 Connected Class||Live Web||10:00 AM-06:00 PM EET||English||1,120 EUR|
|27-28 MAI 2020 Connected Class||Live Web||10:00 AM-06:00 PM EEST||English||1,120 EUR|
|29-30 IUL 2020 Connected Class||Live Web||10:00 AM-06:00 PM EEST||English||1,120 EUR|
|18-19 NOI 2020 Connected Class||Live Web||10:00 AM-06:00 PM EET||English||1,120 EUR|