🎥 Meetup #AperiTech Online Edition 15/04/2020 - GraphRM - Graph ML + State-driven GraphViz
👁 1 раз ⏳ 4442 сек.
Meetup #AperiTech della Community di GraphRM

Speakers:
- Fischer (Fujitsu Laboratories)
- Wing Au(Fujitsu Laboratories)
"Applying Graph Machine Learning to Enterprise Business Problems"
Jeff Fujitsu’s research labs have worked on graph-based Machine Learning from both a theoretical and an applications perspective. In this talk, we’ll describe Fujitsu’s Deep Tensor technology for graph ML and highlight our experiences with applying graph-ML to business problems.

- Kevin Naughten (Cambridge Intelligence)

​A Gentle Introduction to Degrees of Freedom in Machine Learning - Machine Learning Mastery

🔗 A Gentle Introduction to Degrees of Freedom in Machine Learning - Machine Learning Mastery
Degrees of freedom is an important concept from statistics and engineering. It is often employed to summarize the number of values used in the calculation of a statistic, such as a sample statistic or in a statistical hypothesis test. In machine learning, the degrees of freedom may refer to the number of parameters in the model, such as the number of coefficients

​Training with quantization noise for extreme model compression

Quant-Noise is a new technique to enable extreme compression of models that still deliver high performance when deployed in practical applications.

https://ai.facebook.com/blog/training-with-quantization-noise-for-extreme-model-compression/

Paper: https://arxiv.org/abs/2004.07320

GitHub: https://github.com/pytorch/fairseq/tree/master/examples/quant_noise
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Training with quantization noise for extreme model compression
Quant-Noise is a new technique to enable extreme compression of state-of-the-art NLP and CV models without significantly affecting performance.

​Batch Normalization In Neural Networks (Code)

🔗 Batch Normalization In Neural Networks (Code)
Implemented With TensorFlow (Keras)

В видео разбирается использование Logistic Regression.

https://www.youtube.com/watch?v=zM4VZR0px8E&feature=youtu.be

🎥 Machine Learning Tutorial Python - 8: Logistic Regression (Binary Classification)
👁 1 раз ⏳ 1159 сек.
Logistic regression is used for classification problems in machine learning. This tutorial will show you how to use sklearn logisticregression class to solve binary classification problem to predict if a customer would buy a life insurance. At the end we have an interesting exercise for you to solve.
Usually there are two types of machine learning problems (1) Linear regression where prediction value is continuous (2) Classification where predicted value is categorical. Logistic regression is used for clas

​Нейросети для детей: объясняем максимально просто

🔗 Нейросети для детей: объясняем максимально просто
Всем привет. Ни для кого не секрет, что практически все статьи в нашем блоге публикуются к запуску того или иного курса. Следующую статью можно было бы приурочит...

Лекции Машинное обучение

🎥 Лекция 1 | Машинное обучение | Лекториум
👁 15 раз ⏳ 1456 сек.
Лекция 1 | Курс: Машинное обучение | Автор: Сергей Николенко | Организаторы: Computer Science клуб при ПОМИ РАН, Казанский федеральный университет

Смотрите это видео на Лекториуме: https://www.lektorium.tv/node/37035

Смотрите другие лекции курса «Машинное обучение»: https://www.lektorium.tv/node/37036

Подписывайтесь на канал: https://www.lektorium.tv/ZJA
Следите за новостями:
https://vk.com/openlektorium
https://www.facebook.com/openlektorium

🎥 Лекция 2 | Машинное обучение | Лекториум
👁 2 раз ⏳ 1923 сек.
Лекция 2 | Курс: Машинное обучение | Автор: Сергей Николенко | Организаторы: Computer Science клуб при ПОМИ РАН, Казанский федеральный университет

Смотрите это видео на Лекториуме: https://www.lektorium.tv/node/37037

Смотрите другие лекции курса «Машинное обучение»: https://www.lektorium.tv/node/37036

Подписывайтесь на канал: https://www.lektorium.tv/ZJA
Следите за новостями:
https://vk.com/openlektorium
https://www.facebook.com/openlektorium

🎥 Лекция 3 | Машинное обучение | Лекториум
👁 2 раз ⏳ 1282 сек.
Лекция 3 | Курс: Машинное обучение | Автор: Сергей Николенко | Организаторы: Computer Science клуб при ПОМИ РАН, Казанский федеральный университет

Смотрите это видео на Лекториуме: https://www.lektorium.tv/node/37038

Смотрите другие лекции курса «Машинное обучение»: https://www.lektorium.tv/node/37036

Подписывайтесь на канал: https://www.lektorium.tv/ZJA
Следите за новостями:
https://vk.com/openlektorium
https://www.facebook.com/openlektorium

​Анализ библиотеки ИИ ботов из Quake 3

🔗 Анализ библиотеки ИИ ботов из Quake 3
Изучение исходного кода ИИ уже выпущенных игр — превосходный способ изучения хитростей на реальных примерах. Quake 3 Arena — интересный образец, потому что код...

​Boosting performance with XGBoost

🔗 Boosting performance with XGBoost
In this blog, we are going to see how XGBoost works and some of the important features of XGBoost with the help of an example.

​How does data science create value for firms?

🔗 How does data science create value for firms?
Don’t focus on technologies, roles, and org charts. Think instead about how to make data science a core competency of your organization.

🎥 ArcGIS Pro: Your Spatial Data Science Workstation
👁 1 раз ⏳ 1043 сек.
Combining exploratory data analysis, visualization, ArcPy, 'arcgis', machine learning, deep learning, and Notebooks, ArcGIS Pro is a holistic system to solve data science problems. Learn how to build workflows which rely on a hybrid approach of leveraging the deep Python data science ecosystem in rich geoprocessing tools to access both local and enterprise data. See how adding Notebooks to your Pro projects allows you to fully utilize your local resources for interactive analysis results, and build tools in

🎥 Zero to Deep Learning Webinar / Get started with Machine Learning and Deep Learning / Covid 19
👁 1 раз ⏳ 4413 сек.
Zero to Deep Learning webinar on machine learning and COVID-19.

Find out more: https://www.zerotodeeplearning.com

This webinar covers:
- State of AI in 2020
- AI VS COVID-19
- COVID-19 Impact
- Zero to Deep Learning Online
- Hands-on COVID-19 data analysis with Python

🎥 Stock Prediction using Machine Learning and Python | Machine Learning Training | Edureka
👁 2 раз ⏳ 1685 сек.
🔥NIT Warangal Post Graduate Program in AI & Machine Learning with Edureka: https://www.edureka.co/nitw-ai-ml-pgp
This Edureka "Stock Prediction using Machine Learning" takes you through the basic process of predicting the trends of stock prices using machine learning architecture of LSTM while also making use of prominent Python Libraries such as Tensorflow, Keras, etc. Topics covered in the tutorial are as follow:
01:30 Introduction to Stock Prediction
03:00 LSTM Architecture
05:35 Stock Prediction Model
2

​The Iris Dataset — A Little Bit of History and Biology

🔗 The Iris Dataset — A Little Bit of History and Biology
Data can make more sense if we know the stories behind the data.

​How I taught my computer to play Spot it! using OpenCV and Deep Learning

https://towardsdatascience.com/how-i-learned-my-computer-to-play-spot-it-using-opencv-and-deep-learning-ad1f017a3ec3

Habr ru: https://habr.com/ru/company/otus/blog/498800/

Code: https://github.com/henniedeharder/spotit/tree/master/DeepLearningSpotIt

🔗 How I taught my computer to play Spot it! using OpenCV and Deep Learning
Some fun with computer vision and CNNs with a small dataset.

​Building a Real Time Emotion Detection with Python

https://morioh.com/p/801c509dda99

Code: https://github.com/Dhanush45/Realtime-emotion-detectionusing-python

Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Building a Real Time Emotion Detection with Python
In this article, we will discuss creating a Python program to detect real-time emotion of a human being using the camera.

🎥 Машинное обучение 2, ПМИ — лекция 13
👁 4 раз ⏳ 4216 сек.
Лекция по ранжированию и обобщённым линейным моделям

Преподаватель — Евгений Соколов

Курс "Машинное обучение 2", программа "Прикладная математика и информатика", НИУ ВШЭ

​Распознавание документов и лиц: объединение во имя свободы или шаг к цифровой диктатуре?

🔗 Распознавание документов и лиц: объединение во имя свободы или шаг к цифровой диктатуре?
Распространение по миру вируса COVID-19 вызвало резкое изменение паттернов потребительского поведения. В условиях роста панических настроений и предписаний соблю...

​Автор статьи рассказывает об устройстве некоторых моделей машинного обучения.

https://towardsdatascience.com/machine-learning-models-explained-to-a-five-year-old-f2f540d9dcea

🔗 Machine Learning Models Explained to a Five-year-old
Explaining How ML Models Work as Simply as I Can

​Yolo v4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used) http://pjreddie.com/darknet/

https://github.com/AlexeyAB/darknet
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 AlexeyAB/darknet
Windows and Linux version of Darknet Yolo v4 (v3/v2) Neural Networks for object detection (Tensor Cores are used) - AlexeyAB/darknet