https://habr.com/ru/company/sibur_official/blog/437974/

Как победить в цифровом WorldSkills? На практическом примере

#machinelearning #neuralnets #deeplearning #машинноеобучение

Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data

​A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNs

Paper https://arxiv.org/abs/1901.00945

#Neurons #Cognition #MachineLearning

🔗 A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrai
The visual system is hierarchically organized to process visual information in successive stages. Neural representations vary drastically across the first stages of visual processing: at the output of the retina, ganglion cell receptive fields (RFs) exhibit a clear antagonistic center-surround structure, whereas in the primary visual cortex, typical RFs are sharply tuned to a precise orientation. There is currently no unified theory explaining these differences in representations across layers. Here, using a deep convolutional neural network trained on image recognition as a model of the visual system, we show that such differences in representation can emerge as a direct consequence of different neural resource constraints on the retinal and cortical networks, and we find a single model from which both geometries spontaneously emerge at the appropriate stages of visual processing. The key constraint is a reduced number of neurons at the retinal output, consistent with the anatomy of the optic nerve as a stri

​Supervised vs Unsupervised vs Reinforcement Learning | Data Science Certification Training | Edureka

🔗 Supervised vs Unsupervised vs Reinforcement Learning | Data Science Certification Training | Edureka
(** Python Data Science Training: https://www.edureka.co/python **) In this video on Supervised vs Unsupervised vs Reinforcement learning, we’ll be discussin...

​Building a Predictive Model with R in SQL Server Machine Learning Services

🔗 Building a Predictive Model with R in SQL Server Machine Learning Services
Free trainings every Tuesday at 11am EST: http://pragmaticworks.com/Training/Courses#type=Free This webinar will discuss R and Python integration with SQL Se...

​Начинаем работу с Azure Machine Learning service

Сегодня рассмотрим нашу пятую итерацию по созданию продукта для машинного обучения. Чтобы подойти к этой теме, кратко напомним о предыдущих продуктах и их состоянии на текущий момент. Рассмотрим только полностью интегрированные решения, которые позволяют пройти путь от расчета модели до использования в реальных кейсах в одном полноценном продукте.

🔗 Начинаем работу с Azure Machine Learning service
Сегодня рассмотрим нашу пятую итерацию по созданию продукта для машинного обучения. Чтобы подойти к этой теме, кратко напомним о предыдущих продуктах и их...

​I Built My Own Self-Driving Car. Part #1

In this part of article I am going to build a very basic car detection classifier using Python and OpenCV. There is a variety of different object detection and classification techniques and I am going to pay particular attention to the use of Haar Cascades. However, the Haar Cascade classification itself would be covered very briefly in this particular article.

#programming #IT #artificialintellegence #developer #HaarCascade #Python #OpenCV #MadDevs

https://blog.maddevs.io/i-built-my-own-self-driving-car-part-1-4478551ee205

🔗 I Built My Own Self-Driving Car. Part #1 – Mad Devs

​Другой GitHub: репозитории по Data Science, визуализации данных и глубокому обучению

Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data

🔗 Другой GitHub: репозитории по Data Science, визуализации данных и глубокому обучению

​Machine Learning with TensorFlow

Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data

📝 Machine Learning with TensorFlow.pdf - 💾6 063 043

🎥 Tiresias: Predicting Security Events Through Deep Learning
👁 1 раз ⏳ 1427 сек.
Previous research in predicting malicious events only looked at binary outcomes (eg. whether an attack would happen or not), but not at the specific steps that an attacker would undertake. To fill this gap we present Tiresias xspace, a system that leverages Recurrent Neural Networks (RNNs) to predict future events on a machine, based on previous observations.
Read this paper in the ACM Digital Library: https://dl.acm.org/citation.cfm?id=3243811

🎥 10 глупых вопросов РУКОВОДИТЕЛЮ ЯНДЕКС.ПОИСКА
👁 6 раз ⏳ 1173 сек.
Новый гость "10 глупых вопросов" – руководитель Поиска Яндекса Андрей Стыскин. Мы задали Андрею самые глупые вопросы о работе Поиска, личных данных и получили на них умные ответы.
Подписка Яндекс.Плюс на месяц (пробный период) для всех подписчиков канала ЖИЗА: https://ya.cc/52uOI

ЖИЗА в Instagram: https://www.instagram.com/zhiza_show

FAQ – почему мы не озвучиваем вопросы: https://goo.gl/X1mJZV

Другие выпуски «10 глупых вопросов»:
-ветеринар https://goo.gl/WBjJQd
-мультипликатор https://goo.gl/n7obfz
-пр

Introducing Snorkel
https://towardsdatascience.com/introducing-snorkel-27e4b0e6ecff?source=collection_home---4------2---------------------

🎥 Neural networks interactively - right in your browser! - Piotr Migdał - code::dive 2018
👁 1 раз ⏳ 3840 сек.
Deep learning (artificial neural networks) is progressing at a rapid pace. In the last few years, image recognition performance went from not useful to on a par with human level. Lately, AlphaGo Zero not only beat human masters, but was able to do so entirely learning by playing with itself. And it keeps going; something that was an original discovery 6 months ago may have become an industry baseline.

Moreover, it is relatively easy to start using deep learning - using Python libraries such as Keras or PyT

AI Learns Real-Time Defocus Effects in VR

Наш телеграмм канал - https://yangx.top/ai_machinelearning_big_data

https://www.youtube.com/watch?v=Ljgszx4tudo

🎥 AI Learns Real-Time Defocus Effects in VR
👁 1 раз ⏳ 260 сек.
The paper "DeepFocus: Learned Image Synthesis for Computational Displays" and its source code is available here:
https://research.fb.com/publications/deepfocus-siggraph-asia-2018/
https://www.oculus.com/blog/introducing-deepfocus-the-ai-rendering-system-powering-half-dome/
https://github.com/facebookresearch/DeepFocus

Pick up cool perks on our Patreon page:
› https://www.patreon.com/TwoMinutePapers

We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
313V, Alex Haro,

​Mapping knowledge with digital tools to solve healthcare problems in the 21st century

https://towardsdatascience.com/mapping-knowledge-with-digital-tools-to-solve-healthcare-problems-in-the-21st-century-21a19a51c81d?source=collection_home---4------1---------------------

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​Открытый урок «Машинное обучение для всех»

🔗 Открытый урок «Машинное обучение для всех»
Вебинар по Data Science с участием преподавателя Moscow Coding School.

​ABY3: A Mixed Protocol Framework for Machine Learning

🔗 ABY3: A Mixed Protocol Framework for Machine Learning
Machine learning is widely used to produce models for a range of applications and is increasingly offered as a service by major technology companies. However...

​Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!

🔗 Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!
This meetup was recorded in Mountain View, California on January 24th 2019. Slides from the meetup can be viewed here: https://www.slideshare.net/0xdata/get-...

s this the BEST BOOK on Machine Learning? Hands On Machine Learning Review

🎥 Is this the BEST BOOK on Machine Learning? Hands On Machine Learning Review
👁 1 раз ⏳ 331 сек.
Hands On Machine Learning with Scikit Learn and Tensorflow published by O'Reilly and written by Aurelien Geron could just be the best practical book on machine learning. In this review I explain why.

You can buy the book from my Amazon Page ►https://www.amazon.com/shop/pythonprogrammer (affiliate links)

►Subscribe to my YouTube Channel http://bit.ly/2LCdOy1

SUPPORT MY CHANNEL
►Buy me a coffee https://www.ko-fi.com/S6S7LZYP

Programming Learning Resources

Coursera https://www.coursera.org/specializations

🎥 Machine Learning With Tensor Flow | Recurrent Neural Networks | Part 3| Eduonix
👁 1 раз ⏳ 980 сек.
A recurrent neural network (RNN) is a type of artificial neural network commonly used in speech recognition and natural language processing (NLP). RNNs are designed to recognize a data's sequential characteristics and use patterns to predict the next likely scenario. In this video, you will go through the Basics and give the overall explanation of what it is and how it works. Let's learn!!

Want to learn Machine Learning With TensorFlow in Detail? Check out our course Machine Learning With TensorFlow The Pr