Voltar para Introduction to Deep Learning

4.6

657 classificações

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157 avaliações

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....

por YG

•Jan 28, 2018

This is a very hands on Deep Learning class. Like the design of programming assignments a lot. It's very instructive as well as challenging! Great course. I would recommend it!

por AS

•Mar 26, 2018

Great course! The faculty does an excellent job in explaining some difficult to understand concepts. The discussion forum is very active and the course community is helpful.

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157 avaliações

por Darya Loseva

•Dec 14, 2018

In general the course is good, it gives you the idea of different neural networks, their usage and a bit of their inner math. The only thing I didn't really like: most programming assighnments contain large precoded parts, which are difficult to understand. For me it would be more useful, if assighnments wouldn't be so difficult, but I had to code myself.

por Alexander

•Dec 13, 2018

Tell more about TensorFlow and Keras. It was hard to finish final project due to lack of the knowledge in that area.

por Ravindran Mohanavelu

•Dec 04, 2018

Good course. More detailed lectures may have been helpful.

por Juan Manuel Castro Arnez

•Dec 04, 2018

Great amazing high level introduction, with additional resources to reinforce if u are stuck.

por Oleg Ovcharenko

•Dec 01, 2018

Useful course, whereas it is not always clear how to complete homeassignments

por Radishevski Vladislav

•Nov 27, 2018

The course is good enough, but lecturer Aleksendr Panin speaks too quickly and anyway with a strong accent. Fast does not mean good

por Firas Baba

•Nov 26, 2018

One of the best courses of deep learning !!

por Andres Velasquez

•Nov 23, 2018

nice really hard course.

por Paul Émile DUGNAT

•Nov 20, 2018

Such a nice course, which is far more that an "introduction". Thanks

por Igor Palmieri

•Nov 19, 2018

Strongly recommended for those interested in current state of machine learning algorithms

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