A foundation in statistics is required to be effective as a machine learning practitioner. The book

Hello! My name is Artur Kuzin, and I’m a Lead Data Scientist at Dbrain. In the past, I was a researcher in the field of Micro and…

A large part of applied machine learning is about running controlled experiments to discover what algorithm or algorithm configuration to use on a predictive modeling problem. A challenge is that there are aspects of the problem and the algorithm called confounding…

With all the excitement over neural networks and deep-learning techniques, it’s easy to imagine that the world of computer science consists of little else. Neural networks, after all, have begun to outperform humans in tasks such as object and face recognition…

Batch Normalisation does NOT reduce internal covariate shift. This posts looks into why internal covariate shift is a problem and how batch normalisation is used to address it.

Detect pairs of objects in particular relationships.

In this post, I'll discuss an overview of deep learning techniques for object detection using convolutional neural networks. Object detection is useful for understanding what's in an image, describing both what is in an image and where those objects are found.

The choice of a statistical hypothesis test is a challenging open problem for interpreting machine learning results. In his widely cited 1998 paper, Thomas Dietterich recommended the McNemar's test in those cases where it is expensive or impractical to train…

Американский союз гражданских свобод (American Civil Liberties Union, ACLU) продолжает кампанию против использования систем распознавания лиц федеральными аген...

Simple Tensorflow implementation of FusionGAN (CVPR 2018) - taki0112/FusionGAN-Tensorflow

Perhaps one of the most widely used statistical hypothesis tests is the Student's t test.

Because you may use this test yourself someday, it is important to have a deep understanding of how the test works. As a developer, this understanding is best achieved…

Mail.ru уже не первый год проводит чемпионаты по машинному обучению, каждый раз задача по-своему интересна и по-своему сложна. Я участвую в соревнованиях четверт...

Matt Hergott’s Deep Learning Blog

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

The fast.ai co-founder has the 105th score in Kaggle's plant classification contest, but he's dropping. Why? His students are beating him. Learn their techniques.

Python continues to take leading positions in solving data science tasks and challenges. Last year we made a blog post overviewing the…