Autoencoders: How Neural Networks Learn to Compress, Denoise and Detect Anomalies

9 November 2026
автоэнкодер

Autoencoders: How Neural Networks Learn to Compress, Denoise and Detect Anomalies

An autoencoder is a neural network that learns to copy its input to its output through a narrow bottleneck. Because it cannot simply pass every number through, it has to…

Supervised vs Unsupervised vs Reinforcement Learning: Differences and Examples

27 October 2026
обучение с без учителя, с подкреплением

Supervised vs Unsupervised vs Reinforcement Learning: Differences and Examples

Machine learning algorithms are usually grouped by how they learn, and in particular by what kind of feedback they get during training. In supervised learning the model learns from examples…

Microsoft DragNUWA: Video Generation via Object Trajectories

15 January 2024

Microsoft DragNUWA: Video Generation via Object Trajectories

Microsoft has released the DragNUWA weights – a cross-domain video generation model that offers more precise control over the resulting output compared to similar models. Control is achieved by simultaneously…

DeepMind GNoME Discovered 2 Million New Materials

3 December 2023

DeepMind GNoME Discovered 2 Million New Materials

DeepMind has developed the graph neural network GNoME, predicting material stability. GNoME has identified 2.2 million new materials, with 380 thousand deemed stable for application in developing computer chips, batteries,…

14 Free Courses on Machine Learning, Data Science, Data Analysis, and Python

30 August 2023
free machine learning data science analysis python courses

14 Free Courses on Machine Learning, Data Science, Data Analysis, and Python

The prevailing trend in online education is the rise of Massive Open Online Courses (MOOCs). Free courses on machine learning, data science, data analysis, and Python are readily available, based…

LIMA: Pretraining Method on 1000 Examples Achieved GPT4-Level Accuracy

31 May 2023
LIMA LLAMA

LIMA: Pretraining Method on 1000 Examples Achieved GPT4-Level Accuracy

Language models typically undergo two stages of training: unsupervised pretraining and fine-tuning to specific tasks and user preferences. The novel LIMA method (Less Is More for Alignment) challenges the traditional…

Lang: analysis of customer dialogues with support service

28 May 2022

Lang: analysis of customer dialogues with support service

Startup Lang has developed a system that integrates with customer support and CRM to automatically recognize the topic of conversation and identify trends in the reasons for customer requests. The…

TracIn: a way to evaluate the impact of specific data on model predictions

10 February 2021

TracIn: a way to evaluate the impact of specific data on model predictions

TracIn is a scalable method for assessing the impact of individual features in data on predictions. The idea behind TracIn is to track the learning process of the model to…

Deep Clustering Approach for Image Classification Task

20 September 2018
deepcluster facebook

Deep Clustering Approach for Image Classification Task

The clustering of images seems to be a well-researched topic. But in fact, little work has been done to adapt it to the end-to-end training of visual features on large-scale…

Unsupervised Attention-Guided Image-to-Image Translation

30 July 2018
Unsupervised Attention-Guided Image-to-Image Translation

Unsupervised Attention-Guided Image-to-Image Translation

Image-to-image translation is the task of mapping an image from a source domain to a target domain. Applications include image colorization, image super-resolution, style transfer, domain adaptation and data augmentation. Most of the approaches require…