Acerca de este Curso
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Inglés (English)

Subtítulos: Inglés (English), Coreano

Habilidades que obtendrás

Recurrent Neural NetworkTensorflowConvolutional Neural NetworkDeep Learning

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel avanzado

Inglés (English)

Subtítulos: Inglés (English), Coreano

Programa - Qué aprenderás en este curso

Semana
1
5 horas para completar

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.

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9 videos (Total 63 minutos), 2 readings, 3 quizzes
9 videos
Course intro6m
Linear regression9m
Linear classification10m
Gradient descent5m
Overfitting problem and model validation6m
Model regularization5m
Stochastic gradient descent5m
Gradient descent extensions9m
2 lecturas
Welcome!5m
Hardware for the course10m
2 ejercicios de práctica
Linear models6m
Overfitting and regularization8m
Semana
2
6 horas para completar

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.

...
9 videos (Total 85 minutos), 3 readings, 4 quizzes
9 videos
Chain rule7m
Backpropagation9m
Efficient MLP implementation13m
Other matrix derivatives5m
What is TensorFlow10m
Our first model in TensorFlow10m
What Deep Learning is and is not8m
Deep learning as a language6m
3 lecturas
Optional reading on matrix derivatives1m
TensorFlow reading1m
Keras reading1m
2 ejercicios de práctica
Multilayer perceptron10m
Matrix derivatives20m
Semana
3
5 horas para completar

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.

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6 videos (Total 59 minutos), 3 quizzes
6 videos
Our first CNN architecture10m
Training tips and tricks for deep CNNs14m
Overview of modern CNN architectures8m
Learning new tasks with pre-trained CNNs5m
A glimpse of other Computer Vision tasks8m
1 ejercicio de práctica
Convolutions and pooling10m
Semana
4
4 horas para completar

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.

...
9 videos (Total 81 minutos), 3 quizzes
9 videos
Autoencoders 1015m
Autoencoder applications9m
Autoencoder applications: image generation, data visualization & more7m
Natural language processing primer10m
Word embeddings13m
Generative models 1017m
Generative Adversarial Networks10m
Applications of adversarial approach11m
1 ejercicio de práctica
Word embeddings8m
4.6
209 revisionesChevron Right

29%

comenzó una nueva carrera después de completar estos cursos

34%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

14%

consiguió un aumento de sueldo o ascenso

Principales revisiones sobre Introduction to Deep Learning

por AKJun 2nd 2019

one of the best courses I have attended. clear explanation, clear examples, amazing quizzes & Programming Assignment this course is advanced level, don't enroll it if you are a new starter.

por SSJul 20th 2018

Fantastic course.In fact, I think it,s not a easy thing to accomplish all the assignments with this course.\n\nI got a lot of gains through this course. Thanks for all the instructors.

Instructores

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Evgeny Sokolov

Senior Lecturer
HSE Faculty of Computer Science
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Andrei Zimovnov

Senior Lecturer
HSE Faculty of Computer Science
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Alexander Panin

Lecturer
HSE Faculty of Computer Science
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Ekaterina Lobacheva

Senior Lecturer
HSE Faculty of Computer Science
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Nikita Kazeev

Researcher
HSE Faculty of Computer Science

Acerca de National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) 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. Learn more on www.hse.ru...

Acerca del programa especializado Aprendizaje automático avanzado

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....
Aprendizaje automático avanzado

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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