The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding. The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks. Learners will study all popular building blocks of neural networks including fully connected layers, convolutional and recurrent layers.
Ce cours fait partie de la Spécialisation Apprentissage automatique avancé
166 464 déjà inscrits
Offert par
Spécialisation Apprentissage automatique avancéUniversité HSEÀ propos de ce cours
95 640 consultations récentes
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 7 dans le
Niveau avancé
Approx. 34 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol
Compétences que vous acquerrez
Recurrent Neural NetworkTensorflowConvolutional Neural NetworkDeep Learning
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 1 sur 7 dans le
Niveau avancé
Approx. 34 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Italien, Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol
Offert par
Université HSE
HSE University is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more.
Programme du cours : ce que vous apprendrez dans ce cours
6 heures pour terminer
Introduction to optimization
Welcome to the "Introduction to Deep Learning" course! In the first week you'll learn about linear models and stochatic optimization methods. Linear models are basic building blocks for many deep architectures, and stochastic optimization is used to learn every model that we'll discuss in our course.
6 heures pour terminer
10 vidéos (Total 64 min), 4 lectures, 3 quiz
5 heures pour terminer
Introduction to neural networks
This module is an introduction to the concept of a deep neural network. You'll begin with the linear model and finish with writing your very first deep network.
5 heures pour terminer
9 vidéos (Total 85 min), 3 lectures, 4 quiz
6 heures pour terminer
Deep Learning for images
In this week you will learn about building blocks of deep learning for image input. You will learn how to build Convolutional Neural Network (CNN) architectures with these blocks and how to quickly solve a new task using so-called pre-trained models.
6 heures pour terminer
6 vidéos (Total 59 min)
5 heures pour terminer
Unsupervised representation learning
This week we're gonna dive into unsupervised parts of deep learning. You'll learn how to generate, morph and search images with deep learning.
5 heures pour terminer
9 vidéos (Total 81 min)
Avis
Meilleurs avis pour INTRODUCTION TO DEEP LEARNING
par AH29 janv. 2021
Great material, but uses obsolete versions of Tensorflow and needs updating generally. Challenging but educational labs. Lecturer accents are not too bad and lectures are fairly good. I learned a lot.
par EM22 juin 2020
The overall course quality is very decent with real industry applications. I think if you added some additional lecture videos, the course would be better; sometimes it feels like we are in a rush.
par DK19 sept. 2019
one of the excellent courses in deep learning. As stated its advanced and enjoyed a lot in solving the assignments. looking forward for more such courses especially in Natural language processing
par TP8 août 2020
A very good course and it is truly insightful. This course deals with more on the concepts therefore I have a better understanding of what is really happening when I build deep learning models.
À propos du Spécialisation Apprentissage automatique avancé
This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Une aide financière est-elle possible ?
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.
