The goal of this online 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.
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上級機械学習専門講座HSE Universityこのコースについて
108,173 最近の表示
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における7の1コース
上級レベル
約34時間で修了
英語
字幕：アラビア語, フランス語, ポルトガル語（ヨーロッパ）, イタリア語, ベトナム語, 韓国語, ドイツ語, ロシア語, 英語, スペイン語
習得するスキル
- Recurrent Neural Network
- Tensorflow
- Convolutional Neural Network
- Deep Learning
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における7の1コース
上級レベル
約34時間で修了
英語
字幕：アラビア語, フランス語, ポルトガル語（ヨーロッパ）, イタリア語, ベトナム語, 韓国語, ドイツ語, ロシア語, 英語, スペイン語
提供：
HSE University
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.
シラバス - 本コースの学習内容
6時間で修了
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時間で修了
10件のビデオ （合計64分）, 4 学習用教材, 3 個のテスト
5時間で修了
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時間で修了
9件のビデオ （合計85分）, 3 学習用教材, 4 個のテスト
6時間で修了
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時間で修了
6件のビデオ （合計59分）
5時間で修了
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時間で修了
9件のビデオ （合計81分）
レビュー
INTRODUCTION TO DEEP LEARNING からの人気レビュー
AHにより2021年1月29日
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.
EMにより2020年6月22日
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.
DKにより2019年9月19日
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
AMにより2020年5月28日
The hardest, yet most satisfying course I've ever taken in deep learning, by the end of the course I was doing stuff that was borderline sci-fi and that was just "introduction" to deep learning
上級機械学習専門講座について
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.
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