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Introduction to Deep Learning

Higher School of Economics via Coursera

Overview

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.
Learners will use these building blocks to define complex modern architectures in TensorFlow and Keras frameworks. In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image.

The prerequisites for this course are:
1) Basic knowledge of Python.
2) Basic linear algebra and probability.

Please note that this is an advanced course and we assume basic knowledge of machine learning. You should understand:
1) Linear regression: mean squared error, analytical solution.
2) Logistic regression: model, cross-entropy loss, class probability estimation.
3) Gradient descent for linear models. Derivatives of MSE and cross-entropy loss functions.
4) The problem of overfitting.
5) Regularization for linear models.

Do you have technical problems? Write to us: coursera@hse.ru

Taught by

Nikita Kazeev, Andrei Zimovnov, Alexander Panin, Evgeny Sokolov and Ekaterina Lobacheva

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Reviews

2.7 rating, based on 3 reviews

Start your review of Introduction to Deep Learning

  • Lagom Amine is taking this course right now.

    This is a very nice course, it's part of the advanced machine learning specialization so it would make sense if the lecturers go fast through some mathematical intricacies. lecturers are not obviously native speakers but who cares, they speak clearly...
  • Anonymous

    Anonymous is taking this course right now.

    Teachers speak fast and not understandable. Concepts are not explained well either. Practicals need better explanation and should be strongly related to what is thought in the course
  • Anonymous

    Anonymous is taking this course right now.

    I m learning new course to gain knowledge and it is good questions and videos are also best .it is helpful in my further future to achieve anything in life .

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