DeepPavlov

Чат-боты и голосовые помощники

AI Assistant Talks about Beatles history

Look how AI can control robot’s actions

AI Gets Building Tasks Done in Minecraft

Regular: DeepPavlov Seminars

Regular: DeepPavlov Seminars

DFF фреймворк для создания современных диалоговых систем

Борис Галицкий: Применение дискурсивного анализа текста для организации диалога

Публичный семинар: Методы управления диалогом и определение целей в диалоге

Публичный семинар: Обзор подходов к генерации эмоций в диалоге

Monthly DeepPavlov Community Call

Публичный семинар: Использование баз знаний в вопросно-ответных и диалоговых системах

Публичный семинар: Тренды развития обучения мультимодальных диалоговых моделей

Вебинар о тестовых заданиях для студентов образовательной платформы "Нетология"

How to build simple bots in DF SDK using DF Designer

How to design multiskill AI assistants with DeepPavlov Dream

How to integrate a new component into a Dream-based multiskill AI Assistant

How To Integrate Dream with Amazon Alexa

How To Integrate Dream with Yandex Alice

How To Host an HTTPS Endpoint with a Self-Signed Certificate

How to build DFF Skills in Dream-based multiskill AI Assistants with DF Designer (BETA)

DeepPavlov Community Call #16

DeepPavlov Community Call #15. Russian Edition

Regular: DeepPavlov Seminars

DeepPavlov Community Call #14 US

DeepPavlov Community Call #14 | Russian Edition

Seminar #10. Использование дискурсивного лингвистического представления данных в диалоговых системах

Introducing DFF & DF Designer - Seminar

DeepPavlov Weekly Seminars

Seminar #9. Обзор литературы по использованию графов знаний с языковыми моделями

Seminar #8. Победители Alexa Prize 4 ( Part 2)

DeepPavlov Weekly Seminars

DeepPavlov Community Call #13. Russian Edition

DeepPavlov Community Call #13

Seminar #7. Победители Alexa Prize 4 ( Part 1)

Monthly DeepPavlov Community Call #13 | US Edition

Monthly DeepPavlov Community Call #13 | Russian Edition

DeepPavlov Community Call #12

DeepPavlov Community Call #12. Russian Edition

DeepPavlov Community Call #12

DeepPavlov Community Call #11

DeepPavlov Community Call #11. Russian Edition

DeepPavlov Community Call # 11

DeepPavlov Community Call #11. Russian Edition

DeepPavlov Community Call #10

DeepPavlov Community Call #10. Russian Edition

DeepPavlov Community Call #9

DeepPavlov Community Call #9. Russian Edition

DeepPavlov Community Call #8

DeepPavlov Community Call #8 | US Edition

DeepPavlov Community Call #8. Russian Edition

DeepPavlov Community Call #8 | Russian Edition

Seminar #6. Pattern-exploiting training

DeepPavlov Community Call #7

#11 Штурм конкурса Про//чтение

#10 Вся эта BERTология

#9 Использование DeepPavlov в роботе для контактного центра Electra.AI

#8 DeepPavlov отвечает на вопросы по COVID-19

#7 Применение DeepPavlov в enterprise-приложениях

#5 DeepPavlov в решении государственных задач

#6 From 0.1x to 1.0: Shipping DeepPavlov Library

#4 DeepPavlov в сфере корпоративных событий

#1 DeepPavlov 3.0

#2 From Research to Product: Introducing DeepPavlov Multiskill AI Assistant Platform

#3 AI организует твою личную жизнь

DeepPavlov Community Call #6

Seminar #5. Тензорные программы.Часть 2

DeepPavlov Community Call #5

Seminar #4.Тензорные программы.Часть 1

DeepPavlov Community Call #4

DeepPavlov Community Call #3

DeepPavlov Community Call #2

DeepPavlov Community Call #1

Memory Transformer by Mikhail Burtsev [Summer 2020]

NLP #7: Final projects

Seminar #1. RuBQ: A Russian Dataset for Question Answering over Wikidata

RL #14: Final Projects

RL#13: Distributed RL In the wild

RL#11: Multitask & Transfer RL

RL#12: Memory in Reinforcement Learning

RL#9: Model-Based Reinforcement Learning

Разговорный искусственный интеллект

RL#10: Deep Learning At Scale

NLP Trends 2020

RL#8: Multi Agent Reinforcement Learning

RL#7: RL as Probabilistic Inference

RL#5: Distributional Reinforcement Learning

RL#6: RL for Combinatorial optimization

NLP #6: The next generation of language models.

DeepPavlov для community и бизнеса

RL#4: Evolution Strategies in RL

NLP#5: Recurrent Neural Networks and Language Models

NLP #3-4: Neural Networks. Optimization and Normaization

Alexa Prize Socialbot Grand Challenge 3

DeepPavlov: обзор и взгляд в будущее

Практика применения технологий NLP в контакт-центре провайдера

Для науки и не только: как Сбербанк использует библиотеку DeepPavlov каждый день.

DeepPavlov в сообществе Open Data Science

Как автоматизировать контактный центр ДоДо пиццы

DeepPavlov & DataMonsters

iPavlov для бизнеса. Сценарии применения библиотеки

RL#3: Hierarchical Reinforcement Learning

DeepPavlov on GitHub

RL#2: Imitation Learning and Inverse RL

NLP #2: Neural Networks. Backpropagation

RL#1: Exploration in RL

NLP #1: Word vector representations

AI Journey (2019, Moscow)

Theoretical Deep Learning #2: PAC-bayesian bounds. Part5

Theoretical Deep Learning #2: PAC-bayesian bounds. Part4

Theoretical Deep Learning #2: PAC-bayesian bounds. Part3

Theoretical Deep Learning #2: PAC-bayesian bounds. Part2

Theoretical Deep Learning #2: Worst-case bounds. Part 5. PAC-bayesian bounds. Part1

Theoretical Deep Learning #2: Worst-case bounds. Part 4

Theoretical Deep Learning #2: Worst-case bounds. Part 3

Theoretical Deep Learning #2: Worst-case bounds. Part 2

Theoretical Deep Learning #2: Worst-case bounds. Part 1

Theoretical Deep Learning #2: Introduction

Seminar 10. Unsupervised machine translation

Theoretical Deep Learning. The Information Bottleneck method. Part 2

Theoretical Deep Learning. The Information Bottleneck method. Part 1

Seminar 8. Question answering

Theoretical Deep Learning. Gradient descent dynamics on wide shallow nets

Theoretical Deep Learning. Gradient descent dynamics

Seminar 7. Transformer Is All You Need

Seminar 6. Attention! Machine translation

Theoretical Deep Learning. Spin-glass model

Seminar 5. Transfer Learning in NLP

Theoretical Deep Learning. Loss Landscape of Wide Non-linear Nets

Seminar 4. Recurrent Neural Networks and Language Models

Seminar 3. Neural networks Part 2

Theoretical Deep Learning. Linear ResNets, Shallow Non-linear Nets

Seminar 2. Neural networks Part 1

Theoretical Deep Learning. Loss Landscape of Linear Nets. Part 2

Theoretical Deep Learning. Loss Landscape of Linear Nets. Part 1

Theoretical Deep Learning. Introduction

Seminar 1. Part 3. Word vector representations

Seminar 1. Part 2. Course intro

Seminar 1. Part 1. Conversational Artificial Intelligence.

DL in NLP. Final projects presentation

DL in NLP seminar 10. 2018 is the Year of Transfer Learning in NLP. Part 2

DL in NLP seminar 10. 2018 is the Year of Transfer Learning in NLP

DL in NLP seminar 9: Attention Is All You Need. Transformer networks.

DL in NLP seminar 8: Machine Translation with Attention

DL in NLP seminar 7: Gated RNN and Machine Translation

DL in NLP seminar 6: reccurent neural networks

DL in NLP seminar 5: CNN for NLP

DL in NLP seminar 4. Neural networks 2

DL in NLP seminar 3. Neural networks 1

DL in NLP seminar 2. Word2Vec, GloVe, FastText

DL in NLP seminar 1. Intro to NLP and word embeddings.

DeepHackLab DeepHack.Chat finals

DeepHackLab DeepHack.Chat finals

Denis Yarats. Hierarchical Text Generation and Planning for Strategic Dialogue

DeepHackLab DeepPavlov: Seq2Seq Tutorial

DeepHackLab Attention in Neural Networks

DeepHackLab Social Chit-Chat Bot

DeepHackLab Word Embeddings for Dialogue State Tracking

Day 2. Word embeddings (in Russian)

DeepHackLab Goal-Oriented Bot in DeepPavlov

Day 3. Recurrent Neural Networks - part 1 (in Russian)

DeepHackLab Long term dependencies and modular representations for NLP

DeepHackLab Neural Networks basics

Day 3. Convolutional Neural Networks (in Russian)

Day 1. Introduction to Tensorflow (in Russian)

DeepHackLab Named Entity Recognition with DeepPavlov library

Day 2. Introduction to DeepPavlov library

Day1. Conversational Intelligence: Introduction (in Russian)

DeepHackLab Recurrent Neural Networks part 2

DeepHackLab Goal-Oriented Dialogue Systems

DeepHackLab Named Entity Recognition with DeepPavlov library

DeepHackLab Recurrent Neural Networks

DeepHackLab Convolutional Neural Networks

Day 2. Iulian Serban. MILABOT: A Deep Reinforcement Learning Chatbot

DeepHackLab Introduction to DeepPavlov library

Day 2. Neural Networks basics (in Russian)

DeepHackLab Word embeddings

Day 1. Anna Rumshisky. Long-term dependencies and modular representations for NLP

DeepHackLab Introduction to Tensorflow

DeepHackLab Conversational Intelligence Introduction

DMN2

Dynamic Memory Networks

CNN

Machine Translation & Attention

Advanced RNN

RNN and Language Modelling

Backpropagation & Practical Tips

Word Window Classification and Neural Networks

Word Embeddings II

Word Embeddings I

DeepNLP. Intro

DeepPavlov Early Alpha Demo

DeepHack.Babel Finals. Partisipants short talks and the result announcement

DeepHack.Babel Last lecture

DeepHack.Babel Lecture pre-Last

DeepHack.Babel. Ruslan Salakhutdinov. Representation learning for reading comprehension

DeepHack.Babel. Kyughyung Cho. Continuous representations of language

DeepHack.Babel. Konstantin Anisimovich. Use of parallel data for parsing (IN RUSSIAN)

DeepHack.Babel. Lucia Specia. Predicting the Quality of MT

DeepHack.Babel. Serge Sharoff. Comparable corpora (IN RUSSIAN)

DeepHack.Babel. Eduard Klyshinsky. Homonymy and syntax in different languages (IN RUSSIAN)

DeepHack.Babel. Illia Polosukhin. Attention is all you need

DeepHack.Babel. Maksim Kretov. Optimisation of non-differentiable metrics

DeepHack.Babel. Maxim Khalilov. Machine Translation in industry (IN RUSSIAN)

DeepHack.Babel. Romain Paulus. Recent advancements in Machine Translation

DeepHack.Babel. Qun Liu and Peyman Passban. Neural Machine Translation

DeepHack.Babel. Maja Popovic. Evaluation of Machine Translation.

Dynamic Neural Networks

CNN (2)

CNN

LSTM & GRU

RNNs

BackProp + Practical Tips + Project Advice

Word Window Classification

Word Embeddings II

Word Embeddings I

NLP seminar 1

DeepHack.Turing: FINAL

DeepHack.Turing: Participant reports

DeepHack.Turing: AI in Dialog Systems: Business Use-Cases, Pain & Low Hanging Fruits for R&D

DeepHack.Turing: Tomas Mikolov - Neural Networks for Natural Language Processing

DeepHack.Turing: Maksim Kretov - Applications of RL techniques in NLP: An overview

DeepHack.Turing: Peter Schlecht - How to built a company based on Neural Networks

Андрей Шевченко - GPU серверы

DeepHack.Turing: Mikhail Burtsev - iPavlov: Conversational Intelligence Project

DeepHack.Turing: Konstantin Vorontsov - Topic modeling of transcribed call-center conversations

DeepHack.Turing: Rodrigo Nogueira - Learning to Query

DeepHack.Turing: Pei-Hao Su - Reward Estimation for Dialogue Policy Optimisation

DeepHack.Turing: Zhou Yu - Situated intelligent interactive system

Андрей Шевченко - GPU серверы

DeepHack.Turing: Jason Weston - ParlAI

DeepHack.Turing: Pyry Takala - How to evaluate your dialogue response model

DeepHack.Turing: Danica Damljanovic - Building Dialogue Systems: Challenges and Applications

NLP Seminar: Presentations

NLP Seminar 11

DeepHack.RL: Anton Lokhmotov - Cross-platform performance optimisation of deep learning

NLP Seminar 10

NLP Seminar 9

NLP Seminar 8

NLP Seminar 7

AAE notes

NLP Seminar 6

NLP Seminar 5

NLP Seminar 4

NLP Seminar 3

DL in NLP seminar 2

DeepHack.RL: FINAL GAME

DeepHack.RL: Witali Dunin-Barkowski - Neural roots of deep mind

DeepHack.RL: Andrew Barto - Intrinsically motivated reinforcement learning

DeepHack.RL: Alexander Gasnikov - Безградиентные двухточечные методы для стохастической оптимизации

DeepHack.RL: Andrey Raigorodskiy - Перспективные исследовательские задачи

DeepHack.RL: Gabriel Synnaeve - E2D2: Episodic exploration for deep deterministic policies

DeepHack.RL: Marc Bellemare - The role of density models in reinforcement learning

DeepHack.RL: Tejas Kulkarni - Revisiting successor representations

DeepHack.RL: Andrey Lavrentyev - Neural networks for сyber-security of industrial objects

DeepHack.RL: Yulia Sandamirskaya - Neuronal dynamics and autonomous learning in robotics

DeepHack.RL: Doina Precup - Temporal abstraction in reinforcement learning

DeepHack.RL: Andrey Chertok - Reinforcement learning for market-making: application in trading

DeepHack.RL: Alexey Dosovitskiy - Visuomotor control in 3D environments

DeepHack.RL: Konstantin Vorontsov - Регуляризация матричных разложений

DeepHack.RL: Mikhail Burtsev - Model-based reinforcement learning for alternating environments

NLP семинар 10 (09.12.2016)

NLP семинар 9 (02.12.2016)

RL Семинар 8 (27.11.2016)

NLP Семинар 8 (25.11.2016)

RL Семинар 7 (20.11.2016)

RL Семинар 6

NLP Семинар 7 (11.11.2016)

NLP Семинар (28.10.2016)

RL Семинар 5 (23.10.2016)

NLP Семинар 5 (21.10.2016)

RL Семинар 4 (16.10.2016)

NLP Семинар 4

RL Семинар 3 (09.10.2016)

NLP Семинар 3 (07.10.2016)

RL Семинар 2 (02.10.2016)

NLP Семинар 2 (30.09.2016)

25.09 RL Семинар 1

23.09 NLP Семинар 1

DeepHack.Q&A Dmitry Vetrov – Breaking Sticks and Ambiguities with Adaptive Skip-gram

DeepHack.Q&A Dmitry Vetrov – Breaking Sticks and Ambiguities with Adaptive Skip-gram

DeepHack.Q&A Final 30 minutes

DeepHack.Q&A Rob Fergus – The MazeBase project

DeepHack.Q&A Jonathan Berant – Mapping natural language utterances to logical form

DeepHack.Q&A Alexey Minin – History-consistent recurrent neural networks

DeepHack.Q&A Oriol Vinyals – Sequences in Deep Learning

DeepHack.Q&A Quoc Le – Deep Learning for Language Understanding

DeepHack.Q&A Tomas Mikolov – The Roadmap towards Machine Intelligence

DeepHack.Q&A Wojciech Zaremba – Learning Simple Algorithms from Examples

DeepHack.Q&A Alexey Uzakov – Artificial Intelligence for Robotics, Promobot case

DeepHack.Q&A Anatoly Levenchuk – Machine learning engineering

DeepHack.Q&A Jason Weston – Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems

DeepHack.Q&A Phil Blunsom – Memory, Reading, and Comprehension

DeepHack.Q&A Сергей Белан – Методы увеличения производительности мозга

DeepHack.Q&A Konstantin Vorontsov – Regularization of Topic Models for Question Answering

DeepHack.Q&A Christopher Manning – Compositional Linguistic Représentations

DeepHack.Q&A Kyunghyun Cho – New Territory of Machine Translation

DeepHack.Q&A Альберт Ефимов (Skolkovo Robotics) – The introduction of a start-up part

DeepHack.Q&A Alexey Natekin – Presentation of OpenDataScience Community

DeepHack.Q&A Official opening words

5vision kung fu master

Deep Punx hero

Deep Punx space invaders

Deep Punx kung fu master

5vision hero

5vision space invaders

Life Propagation space invaders

Life Propagation kung fu master

LMM kung fu master

Red pandas hero

Red pandas kung fu master

Red pandas space invaders

LMM space invaders

LMM hero

SkyNet space invaders

SkyNet kung fu master

FastLearning kung fu master

SkyNet hero

Rock Band kung fu master

FastLearning space invaders

FastLearning hero