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…
🎥 Tensorflow Image Classification | Build Your Own Image Classifier In Tensorflow | Edureka
👁 1 раз ⏳ 2071 сек.
👁 1 раз ⏳ 2071 сек.
***AI and Deep Learning using TensorFlow: https://edureka.co/ai-deep-learning-with-tensorflow ***
This Edureka Live video on "Tensorflow Image Classification" will provide you with a comprehensive and detailed knowledge of Image classification and how it can be implemented using Tensorflow. It covers two types of techniques:
1. Normal Neural Network
2. Convolutional Neural Network
-----------------------------------------------------------
Complete Youtube Playlist here: https://bit.ly/2OhZEpz
Deep LeVk
Tensorflow Image Classification | Build Your Own Image Classifier In Tensorflow | Edureka
***AI and Deep Learning using TensorFlow: https://edureka.co/ai-deep-learning-with-tensorflow ***
This Edureka Live video on "Tensorflow Image Classification" will provide you with a comprehensive and detailed knowledge of Image classification and how it…
This Edureka Live video on "Tensorflow Image Classification" will provide you with a comprehensive and detailed knowledge of Image classification and how it…
https://medium.com/@wang.alex.c/introducing-superglue-a-new-hope-against-muppetkind-2779fd9dcdd5
🔗 Introducing SuperGLUE: A New Hope Against Muppetkind
Over the past year, a machine learning models have dramatically improved scores across many language understanding tasks in NLP. ELMo…
🔗 Introducing SuperGLUE: A New Hope Against Muppetkind
Over the past year, a machine learning models have dramatically improved scores across many language understanding tasks in NLP. ELMo…
Medium
Introducing SuperGLUE: A New Hope Against Muppetkind
Over the past year, a machine learning models have dramatically improved scores across many language understanding tasks in NLP. ELMo…
A Complete Guide to Learn R
🔗 A Complete Guide to Learn R
R Programming Technology is an open source programming language. Also, the R programming language is the latest cutting-edge tool. R…
🔗 A Complete Guide to Learn R
R Programming Technology is an open source programming language. Also, the R programming language is the latest cutting-edge tool. R…
Towards Data Science
A Complete Guide to Learn R
R Programming Technology is an open source programming language. Also, the R programming language is the latest cutting-edge tool. R…
Classifying Products as Banned Or Approved using Text Mining- Part II
🔗 Classifying Products as Banned Or Approved using Text Mining- Part II
In this part, we will explain how to optimize the existing Machine Learning model in Part I and the deployment of this ML model using…
🔗 Classifying Products as Banned Or Approved using Text Mining- Part II
In this part, we will explain how to optimize the existing Machine Learning model in Part I and the deployment of this ML model using…
Towards Data Science
Classifying Products as Banned Or Approved using Text Mining- Part II
In this part, we will explain how to optimize the existing Machine Learning model in Part I and the deployment of this ML model using…
🎥 Евгений Разинков. Лекция 3. Регуляризация линейных моделей регрессии (весна, 2019).
👁 1 раз ⏳ 3400 сек.
👁 1 раз ⏳ 3400 сек.
В рамках лекции рассмотрен базовый метод регуляризации линейных моделей регрессии:
- Зачем нужна регуляризация
- Метод Weight Decay.
- Как меняется целевая функция
- Вычисление параметров модели при использовании регуляризации.
Евгений Разинков -- к.ф.-м.н., руководитель отдела машинного обучения и компьютерного зрения Группы компаний FIX, ассистент кафедры системного анализа и ИТ института ВМиИТ Казанского федерального университета.
Информация о лекциях:
http://razinkov.ai
Телеграм-канал с анонсами лекцVk
Евгений Разинков. Лекция 3. Регуляризация линейных моделей регрессии (весна, 2019).
В рамках лекции рассмотрен базовый метод регуляризации линейных моделей регрессии:
- Зачем нужна регуляризация
- Метод Weight Decay.
- Как меняется целевая функция
- Вычисление параметров модели при использовании регуляризации.
Евгений Разинков -- к.ф.-м.н.…
- Зачем нужна регуляризация
- Метод Weight Decay.
- Как меняется целевая функция
- Вычисление параметров модели при использовании регуляризации.
Евгений Разинков -- к.ф.-м.н.…
Speed Up Your Exploratory Data Analysis With Pandas-Profiling
🔗 Speed Up Your Exploratory Data Analysis With Pandas-Profiling
Get an intuition of your data’s structure with just one line of code
🔗 Speed Up Your Exploratory Data Analysis With Pandas-Profiling
Get an intuition of your data’s structure with just one line of code
Medium
Speed Up Your Exploratory Data Analysis With Pandas-Profiling
Get an intuition of your data’s structure with just one line of code
Raising a child vs Training a machine
🔗 Raising a child vs Training a machine
The mom’s point of view on Machine Learning
🔗 Raising a child vs Training a machine
The mom’s point of view on Machine Learning
Towards Data Science
Raising a child vs Training a machine
The mom’s point of view on Machine Learning
🎥 L24/4 Seq2sen with Attention in Python
👁 1 раз ⏳ 638 сек.
👁 1 раз ⏳ 638 сек.
Dive into Deep Learning
UC Berkeley, STAT 157
Slides are at
http://courses.d2l.ai
The book is at
http://www.d2l.ai
Naive Bayes ClassifiersVk
L24/4 Seq2sen with Attention in Python
Dive into Deep Learning
UC Berkeley, STAT 157
Slides are at
http://courses.d2l.ai
The book is at
http://www.d2l.ai
Naive Bayes Classifiers
UC Berkeley, STAT 157
Slides are at
http://courses.d2l.ai
The book is at
http://www.d2l.ai
Naive Bayes Classifiers
Data Minds: Evan Chow — Data Scientist at Snapchat
🔗 Data Minds: Evan Chow — Data Scientist at Snapchat
Data Minds is a series that profiles professionals working with data. In this series, you’ll learn about their story, day-to-day, and…
🔗 Data Minds: Evan Chow — Data Scientist at Snapchat
Data Minds is a series that profiles professionals working with data. In this series, you’ll learn about their story, day-to-day, and…
Towards Data Science
Data Minds: Evan Chow — Data Scientist at Snapchat
Data Minds is a series that profiles professionals working with data. In this series, you’ll learn about their story, day-to-day, and…
🎥 Deep Learning Weekly-1. Neural Ordinary Differential Equations
👁 1 раз ⏳ 4251 сек.
👁 1 раз ⏳ 4251 сек.
Первый доклад в рамках еженедельного семинара DeepLearning Weekly
Код с примером (Julia): https://yadi.sk/d/BKD-Etsjf3fwUQVk
Deep Learning Weekly-1. Neural Ordinary Differential Equations
Первый доклад в рамках еженедельного семинара DeepLearning Weekly
Код с примером (Julia): https://yadi.sk/d/BKD-Etsjf3fwUQ
Код с примером (Julia): https://yadi.sk/d/BKD-Etsjf3fwUQ