ahmedfgad/GARI
🔗 ahmedfgad/GARI
This work introduces a simple project called GARI (Genetic Algorithm for Reproducing Images). GARI reproduces a single image using Genetic Algorithm (GA) by evolving pixel values. - ahmedfgad/GARI
🔗 ahmedfgad/GARI
This work introduces a simple project called GARI (Genetic Algorithm for Reproducing Images). GARI reproduces a single image using Genetic Algorithm (GA) by evolving pixel values. - ahmedfgad/GARI
GitHub
GitHub - ahmedfgad/GARI: GARI (Genetic Algorithm for Reproducing Images) reproduces a single image using Genetic Algorithm (GA)…
GARI (Genetic Algorithm for Reproducing Images) reproduces a single image using Genetic Algorithm (GA) by evolving pixel values. - ahmedfgad/GARI
🎥 Lesson 4. Linear models and Gradient Descent
👁 1 раз ⏳ 1942 сек.
👁 1 раз ⏳ 1942 сек.
Linear models are the base algorithms in machine learning, they are used almost everywhere in production. The are the key for understanding the work of one neuron in neural nets.
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?id=1zxLACGTyzWigd_JkCN76D8GCxyM6LWCf
---
About Deep Learning School at PSAMI MIPT
Official website: https://www.dlschool.org
Github-repo: https://github.com/DLSchool/dlschool_english
About PSAMI MIPT
Official website: https://mipt.ru/english/edu/phyVk
Lesson 4. Linear models and Gradient Descent
Linear models are the base algorithms in machine learning, they are used almost everywhere in production. The are the key for understanding the work of one neuron in neural nets.
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?…
Lecturer: Kirill Golubev (MIPT)
Materials:
https://drive.google.com/open?…
🎥 Tesla Autonomy 3/6: Neural Networks
👁 1 раз ⏳ 2030 сек.
👁 1 раз ⏳ 2030 сек.
Andrej Karpathy, Tesla's deep learning and computer vision expert talks about neural networks.Vk
Tesla Autonomy 3/6: Neural Networks
Andrej Karpathy, Tesla's deep learning and computer vision expert talks about neural networks.
What is Natural Language Processing (NLP)? A bitesize explanation
🔗 What is Natural Language Processing (NLP)? A bitesize explanation
NLP keeps being bounded about as a magic panacea or a digital tower of babel and with many conflicting ideas. I present a quick…
🔗 What is Natural Language Processing (NLP)? A bitesize explanation
NLP keeps being bounded about as a magic panacea or a digital tower of babel and with many conflicting ideas. I present a quick…
Towards Data Science
What is Natural Language Processing (NLP)? A bitesize explanation
NLP keeps being bounded about as a magic panacea or a digital tower of babel and with many conflicting ideas. I present a quick…
🎥 Theoretical Deep Learning. The Information Bottleneck method. Part 1
👁 1 раз ⏳ 5831 сек.
👁 1 раз ⏳ 5831 сек.
In this class we introduce the information bottleneck method. We also discuss what we can learn about the training process of neural nets using this technique.
Find out more: https://github.com/deepmipt/tdl
Our open-source framework to develop and deploy conversational assistants: https://deeppavlov.ai/Vk
Theoretical Deep Learning. The Information Bottleneck method. Part 1
In this class we introduce the information bottleneck method. We also discuss what we can learn about the training process of neural nets using this technique.
Find out more: https://github.com/deepmipt/tdl
Our open-source framework to develop and deploy…
Find out more: https://github.com/deepmipt/tdl
Our open-source framework to develop and deploy…
Разработка поисковой системы на основе векторных представлений слов
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🎥 Разработка поисковой системы на основе векторных представлений слов
👁 1 раз ⏳ 3315 сек.
Наш телеграм канал - tglink.me/ai_machinelearning_big_data
🎥 Разработка поисковой системы на основе векторных представлений слов
👁 1 раз ⏳ 3315 сек.
Основой поисковых систем, существующих на данный момент, является инвертированный индекс, с помощью которого происходит выборка документов для ранжирования. Данный подход имеет ряд недостатков. Например, документы, не имеющие пересечения с запросом, но содержащие похожие (синонимичные) слова, никогда не будут попадать в поисковую выдачу.
На этом семинаре будет показан возможный принципиально другой подход к организации поискового индекса с использованием векторных представлений слов, который мы реализуем вVk
Разработка поисковой системы на основе векторных представлений слов
Основой поисковых систем, существующих на данный момент, является инвертированный индекс, с помощью которого происходит выборка документов для ранжирования. Данный подход имеет ряд недостатков. Например, документы, не имеющие пересечения с запросом, но содержащие…
Mind the Machines: a podcast about data science jobs and the future of AI
🔗 Mind the Machines: a podcast about data science jobs and the future of AI
We’ve learned a lot about the data science job market since we launched SharpestMinds. We’ve interviewed thousands of aspiring data…
🔗 Mind the Machines: a podcast about data science jobs and the future of AI
We’ve learned a lot about the data science job market since we launched SharpestMinds. We’ve interviewed thousands of aspiring data…
Towards Data Science
Mind the Machines: a podcast about data science jobs and the future of AI
We’ve learned a lot about the data science job market since we launched SharpestMinds. We’ve interviewed thousands of aspiring data…
🎥 Deep Learning на пальцах 10 - Recurrent Neural Networks
👁 1 раз ⏳ 5100 сек.
👁 1 раз ⏳ 5100 сек.
Курс: http://dlcourse.ai
Слайды: https://www.dropbox.com/s/eafd6z6sr2ajnka/Lecture%2010%20-%20RNNs%20-%20annotated.pdf?dl=0Vk
Deep Learning на пальцах 10 - Recurrent Neural Networks
Курс: http://dlcourse.ai Слайды: https://www.dropbox.com/s/eafd6z6sr2ajnka/Lecture%2010%20-%20RNNs%20-%20annotated.pdf?dl=0
Security Vulnerabilities of Neural Networks
🔗 Security Vulnerabilities of Neural Networks
What to do when your network thinks everything is an ostrich.
🔗 Security Vulnerabilities of Neural Networks
What to do when your network thinks everything is an ostrich.
Towards Data Science
Security Vulnerabilities of Neural Networks
What to do when your network thinks everything is an ostrich.
MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
🎥 MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
👁 1 раз ⏳ 4055 сек.
🎥 MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
👁 1 раз ⏳ 4055 сек.
Introductory lecture on Human-Centered Artificial Intelligence (MIT 6.S093) I gave on February 1, 2019. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on our GitHub repo.
INFO:
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Slides: http://bit.ly/2IDMd0U
Transcript: http://bit.ly/2IDMkcQ
Playlist: http://bit.ly/deep-learnVk
MIT 6.S093: Introduction to Human-Centered Artificial Intelligence (AI)
Introductory lecture on Human-Centered Artificial Intelligence (MIT 6.S093) I gave on February 1, 2019. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website…
Так сложно найти, легко пропустить и невозможно оформить
🔗 Так сложно найти, легко пропустить и невозможно оформить
Наши правила жизни: начинать название статей с буквы «Т» и искать текстовые заимствования быстро, точно и, самое главное, красиво. Уже больше года мы успешно нах...
🔗 Так сложно найти, легко пропустить и невозможно оформить
Наши правила жизни: начинать название статей с буквы «Т» и искать текстовые заимствования быстро, точно и, самое главное, красиво. Уже больше года мы успешно нах...
Хабр
Так сложно найти, легко пропустить и невозможно оформить
Наши правила жизни: начинать название статей с буквы «Т» и искать текстовые заимствования быстро, точно и, самое главное, красиво. Уже больше года мы успешно нах...
С бородой, в тёмных очках и в профиль: трудные ситуации для компьютерного зрения
🔗 С бородой, в тёмных очках и в профиль: трудные ситуации для компьютерного зрения
Технологии и модели для нашей будущей системы компьютерного зрения создавались и совершенствовались постепенно и в разных проектах нашей компании — в Почте, Об...
🔗 С бородой, в тёмных очках и в профиль: трудные ситуации для компьютерного зрения
Технологии и модели для нашей будущей системы компьютерного зрения создавались и совершенствовались постепенно и в разных проектах нашей компании — в Почте, Об...
Хабр
С бородой, в тёмных очках и в профиль: трудные ситуации для компьютерного зрения
Технологии и модели для нашей будущей системы компьютерного зрения создавались и совершенствовались постепенно и в разных проектах нашей компании — в Почте, Облаке, Поиске. Вызревали как хороший...
🎥 Машинное обучение 9. Нейросети, часть 1
👁 1 раз ⏳ 4419 сек.
👁 1 раз ⏳ 4419 сек.
Лекция 9.04.2019
Лектор: Радослав Нейчев
Снимал: Михаил Кревский
Монтировал: Алексей КозиновVk
Машинное обучение 9. Нейросети, часть 1
Лекция 9.04.2019
Лектор: Радослав Нейчев
Снимал: Михаил Кревский
Монтировал: Алексей Козинов
Лектор: Радослав Нейчев
Снимал: Михаил Кревский
Монтировал: Алексей Козинов
facebookresearch/PyTorch-BigGraph
🔗 facebookresearch/PyTorch-BigGraph
Software used for generating embeddings from large-scale graph-structured data. - facebookresearch/PyTorch-BigGraph
🔗 facebookresearch/PyTorch-BigGraph
Software used for generating embeddings from large-scale graph-structured data. - facebookresearch/PyTorch-BigGraph
GitHub
GitHub - facebookresearch/PyTorch-BigGraph: Generate embeddings from large-scale graph-structured data.
Generate embeddings from large-scale graph-structured data. - facebookresearch/PyTorch-BigGraph
Code Faster with Line-of-Code Completions, Cloudless Processing
🔗 Code Faster with Line-of-Code Completions, Cloudless Processing
Kite is a free autocomplete for Python developers. Code faster with the Kite plugin for your code editor, featuring Line-of-Code Completions and cloudless processing.
🔗 Code Faster with Line-of-Code Completions, Cloudless Processing
Kite is a free autocomplete for Python developers. Code faster with the Kite plugin for your code editor, featuring Line-of-Code Completions and cloudless processing.
Code Faster with Kite
Kite is saying farewell
From 2014 to 2021, Kite was a startup using AI to help developers write code. We have stopped working on Kite, and are no longer supporting the Kite software. Thank you to everyone who used our product, and thank you to our team members and investors who…
Best Deep Learning Research of 2019 So Far
https://medium.com/@ODSC/best-deep-learning-research-of-2019-so-far-7bea0ed22e38
🔗 Best Deep Learning Research of 2019 So Far
We’re just about finished with Q1 of 2019, and the research side of deep learning technology is forging ahead at a very good clip. I…
https://medium.com/@ODSC/best-deep-learning-research-of-2019-so-far-7bea0ed22e38
🔗 Best Deep Learning Research of 2019 So Far
We’re just about finished with Q1 of 2019, and the research side of deep learning technology is forging ahead at a very good clip. I…
Medium
Best Deep Learning Research of 2019 So Far
We’re just about finished with Q1 of 2019, and the research side of deep learning technology is forging ahead at a very good clip. I…
🎥 Stanford Seminar - Deep Learning for Medical Diagnoses
👁 1 раз ⏳ 3394 сек.
👁 1 раз ⏳ 3394 сек.
Pranav Rajpurkar
Stanford University
April 17, 2019
The use of algorithms in clinical care demands a very high performance level for accurate detection and classification of disease. Deep learning (DL) offers a powerful toolkit necessary to handle the complex variations present in medical data, which traditional statistical or machine learning approaches have historically been unable to capture. In this talk, I will describe the challenges and approaches for the development of high-performance DL algoritVk
Stanford Seminar - Deep Learning for Medical Diagnoses
Pranav Rajpurkar
Stanford University
April 17, 2019
The use of algorithms in clinical care demands a very high performance level for accurate detection and classification of disease. Deep learning (DL) offers a powerful toolkit necessary to handle the…
Stanford University
April 17, 2019
The use of algorithms in clinical care demands a very high performance level for accurate detection and classification of disease. Deep learning (DL) offers a powerful toolkit necessary to handle the…
OpenAI Bot Crushes Dota 2 Champions And This is Just the Beginning
🔗 OpenAI Bot Crushes Dota 2 Champions And This is Just the Beginning
Machines, like humans, learn best when they’re beaten
🔗 OpenAI Bot Crushes Dota 2 Champions And This is Just the Beginning
Machines, like humans, learn best when they’re beaten
Towards Data Science
OpenAI Bot Crushes Dota 2 Champions And This is Just the Beginning
Machines, like humans, learn best when they’re beaten
Hyperparameter optimization in python. Part 1: Scikit-Optimize.
🔗 Hyperparameter optimization in python. Part 1: Scikit-Optimize.
In this blog series, I am comparing python HPO libraries. Before reading this post, I would highly advise that you read Part 0…
🔗 Hyperparameter optimization in python. Part 1: Scikit-Optimize.
In this blog series, I am comparing python HPO libraries. Before reading this post, I would highly advise that you read Part 0…
Towards Data Science
Hyperparameter optimization in python. Part 1: Scikit-Optimize.
In this blog series, I am comparing python HPO libraries. Before reading this post, I would highly advise that you read Part 0…