​Фейковый Слак, который позволяет тестировать ваших ботов без внешних зависимостей

🔗 Знакомство с mad-fake-slack (альфа версия)
mad-fake-slack — это прежде всего инструмент для тестирования вашего бота, без использования реальных серверов slack. В будущем это будет…

​DeepFaceLab is a tool that utilizes machine learning to replace faces in videos.

https://github.com/iperov/DeepFaceLab

🔗 iperov/DeepFaceLab
DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. Includes prebuilt ready to work standalone Windows 7,8,10 binary (look readme.md). - iperov/DeepFaceLab

​Using AI to generate recipes from food images

🔗 Using AI to generate recipes from food images
We are releasing the code for a new approach to generating recipes directly from food images. This produces more compelling recipes than retrieval-based approaches and improves performance with respect to previous baselines for ingredient prediction.

🎥 Митап 3: Искусственный интеллект, машинное обучение, нейронные сети / Smart IT ЛитКлуб
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30 мая Андрей Коранчук провел лекцию об искуственный интеллект:
- Основные понятия.
- Нейрон, Персептрон, Нейросеть, TensorFlow
- Прогноз развития рынка.
- Перспективы работы.
- Применение.
- Что нужно знать из математики.
- С чего вообще начать.

Для тех, кто решит начать полный набор ссылок на лекции:
Линейная алгебра
https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/

Вычисления
https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr

Теория вероятности
https://

🎥 Private Cloud со вкусом Public (Дмитрий Лазаренко, Mail.ru Cloud Solutions)
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Запись выступления «Private Cloud со вкусом Public: как это видят интернет-гиганты» — Дмитрий Лазаренко, директор по продукту Mail.ru Cloud Solutions https://mcs.mail.ru, рассказывает о платформе для построения частного облака Mail.ru Private Cloud https://mcs.mail.ru/private-cloud/ и других сервисах Mail.ru Group для бизнеса.

Виртуализация и облака давно на слуху и в обиходе практически любой компании. Все давно научились применять их для решения повседневных задач, но эпоха цифровой трансформации требует

​Nvidia’s New Data Science Workstation — a Review and Benchmark

🔗 Nvidia’s New Data Science Workstation — a Review and Benchmark
Data science is hot.

​Neural Network Optimization

🔗 Neural Network Optimization
Covering optimizers, momentum, adaptive learning rates, batch normalization, and more.

🎥 2019 Van Horn Distinguished Lectures: 3: machine learning of materials structure & synthesis
👁 1 раз ⏳ 4787 сек.
2019 Van Horn Distinguished Lectures: Part 3 - machine learning of materials structure and synthesis.

The Kent R. van Horn Lectureship is an endowed Lectureship at the Case Western Reserve University and dates from 1974. It honours Kent R. van Horn, an alum, who had a distinguished career as a metallurgist, director of research, and ultimately corporate vice-president of Alcoa. Three lectures on varied topics are to be delivered over three successive days. The 2019 lectures were delivered by Gerbrand Cede

Boosting Machine Learning Tutorial | Adaptive Boosting, Gradient Boosting, XGBoost
https://www.youtube.com/watch?v=kho6oANGu_A

🎥 Boosting Machine Learning Tutorial | Adaptive Boosting, Gradient Boosting, XGBoost | Edureka
👁 1 раз ⏳ 1278 сек.
** Machine Learning Certification Training using Python: https://www.edureka.co/python **
This Edureka session will help you understand all about Boosting Machine Learning and boosting algorithms and how they can be implemented to increase the efficiency of Machine Learning models.
The following topics are covered in this session:
01:02 Why Is Boosting Used?
03:47 What Is Boosting?
07:22 How Boosting Algorithm Works?
10:04 Types Of Boosting
14:56 Demo

Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Se

​Understanding Cancer using Machine Learning

🔗 Understanding Cancer using Machine Learning
Use of Machine Learning (ML) in Medicine is becoming more and more important. One application example can be Cancer Detection and Analysis.

​Foundations of Machine Learning

🔗 Foundations of Machine Learning

​Predicting Bus Delays with Machine Learning

http://ai.googleblog.com/2019/06/predicting-bus-delays-with-machine.html

🔗 Predicting Bus Delays with Machine Learning
Posted by Alex Fabrikant, Research Scientist, Google Research Hundreds of millions of people across the world rely on public transit for...

​Machine Learning Cheat Sheet — Unsupervised Learning

🔗 Machine Learning Cheat Sheet — Unsupervised Learning
K-Means Clustering

🎥 Виктор Кандоба, Светлана Завьялова. Робот на линии - автоматизируем поддержку с помощью речевых т
👁 1 раз ⏳ 1961 сек.
- С чего начать внедрение речевых технологий и как продать это бизнесу?
- Из чего состоит голосовой сервис, какие есть инструменты?
- Что разрабатывать самостоятельно, а что лучше переиспользовать, в каком порядке?
- Как выбрать сценарии и проводить эксперименты?

О чем расскажем:
- ASR и TTS. Облачные и back'end технологии, MRСP и API, подводные камни
- Сценарии диалога. С чего начали, как они выглядят в коде, какие данные собирали
NLU. От ключевых слов к машинному обучению
- Результаты. Что получило

🎥 Lesson 13 (2019) - Basics of Swift for Deep Learning
👁 1 раз ⏳ 7970 сек.
NB: Please view videos through course.fast.ai for full notes, searchable transcripts, etc. Please use forums.fast.ai for all questions - don't ask questions in the youtube comments section!

We've just completed building much of the fastai library for Python from scratch. Now we're going to try to repeat the process for Swift! These next two lessons are co-taught by Jeremy along with Chris Lattner, the original developer of Swift, and the lead of the Swift for TensorFlow project at Google Brain.

In today's

​MBA to IBM Data Scientist: Exclusive Interview with Greg Rafferty

🔗 MBA to IBM Data Scientist: Exclusive Interview with Greg Rafferty
TDS talks with Lead Data Scientist at IBM on company’s workflow, internal NLP projects, and getting the first data science job.

🎥 Convolutional Neural Network Tutorial (CNN) | Convolutional Neural Networks With TensorFlow
👁 1 раз ⏳ 7138 сек.
🔥Intellipaat Artificial Intelligence Engineer Master's Course: https://intellipaat.com/artificial-intelligence-masters-training-course/
In this convolutional neural network tutorial you will learn what is convolutional neural networks, various layers in convolutional neural networks with tensorflow and a demo on demo on convolutional neural networks with keras in detail.
#ConvolutionalNeuralNetworkTutorial #ConvolutionalNeuralNetworksWithTensorFlow

📌 Do subscribe to Intellipaat channel & get regular updat

​Positive or Negative? Spam or Not-spam? A simple Text classification problem using Python

🔗 Positive or Negative? Spam or Not-spam? A simple Text classification problem using Python
Do you know how your favorite Email service providers classify the emails you receive as spam or not-spam? It uses text classification to…

​Decision Tree Regression Simplest Example using Python | Machine Learning

🔗 Decision Tree Regression Simplest Example using Python | Machine Learning
How does a Decision tree work on a continous target variable i.e. for a regression variable?
How does it find the point for split?

In this video, I explain how a decision tree regression works. I hope you like it.

Link to the notebook : https://github.com/bhattbhavesh91/decision_tree_regression/blob/master/dt_regression.ipynb

If you do have any questions with what we covered in this video then feel free to ask in the comment section below & I'll do my best to answer those.

If you enjoy these tutorials &