International student hackathon

В субботу завершился месячный конкурс по машинному обучению от mail.ru ML bootcamp 5 . я занял в нем 14ое место . Это уже третий мой конкурс, в котором я выиграл одежду и за время участия у меня...

And how there’s more to it than word embeddings.

Tensorboard helps to train NN models. This article is an overview of tensorboard and a framework for training a neural network using tensorboard with keras.

In the previous post on Support Vector Machines (SVM), we looked at the mathematical details of the algorithm. In this post, I will be discussing the practical implementations of SVM for classification as well as regression.
I will be using the iris dataset…

Key text classification algorithms with use cases and tutorials

Explore a highly effective deep learning approach to sentiment analysis using TensorFlow and LSTM networks.

Dear Friends,

Let’s build a neural network that can do math. In Keras.

Tensorflow implementation of different GANs and their comparisions - sanghoon/tf-exercise-gan

A tensorflow implementation of EAST text detector. Contribute to argman/EAST development by creating an account on GitHub.

The Keras library provides a way to calculate and report on a suite of standard metrics when training deep learning models. In addition to offering standard metrics for classification and regression problems, Keras also allows you to define and report on…

Can you see the resemblance?

A few months ago I posted some results from experiments with highresolution GAN-generated faces. By popular request here is a little more on the approach tak...

Еще одна статья от лица участника школы о проекте, реализованном в рамках очередного выезда: «Я – Дмитрий Пасечнюк, и я хочу поделиться своим исследованием, с...

Introduction:

Tensorboard’s embeddings visualiser is great. You can use it to visualise and explore any set of high dimensional vectors (say, the activations of a hidden layer of a neural net) in a lower-dimensional space.