​Роман Логинов: Мультимоделирование как универсальный способ описания выборки общего вида

🔗 Роман Логинов: Мультимоделирование как универсальный способ описания выборки общего вида
В случае неоднородных данных в машинном обучении использования одной модели недостаточно. Для выявления этого используют комбинации нескольких моделей - муль...

​https://m.youtube.com/watch?v=FDzIafdbTVw

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​Policy Intelligence: Applying Machine Learning and Analytics to Security in GCP (Cloud Next '19)

🔗 Policy Intelligence: Applying Machine Learning and Analytics to Security in GCP (Cloud Next '19)
Cloud environments today are complex. Even when all the information is available, it’s hard to pull it all together to make a good decision. Imagine if your ...

​Наш телеграм канал - tglink.me/ai_machinelearning_big_data

https://towardsdatascience.com/careful-looking-at-your-model-results-too-much-can-cause-information-leakage-95b4517404bc?source=collection_home---4------4---------------------

🔗 Careful! Looking at Your Model Results Too Much Can Cause Information Leakage
It’s always to use as much data as you can when building machine learning models. I think we all are aware of the issue of overfitting…

​Make your own Super Pandas using Multiproc

🔗 Make your own Super Pandas using Multiproc
Increase your data preprocessing speed using parallelization in Pandas

​Наш телеграм канал - tglink.me/ai_machinelearning_big_data
https://machinelearningmastery.com/best-practices-for-preparing-and-augmenting-image-data-for-convolutional-neural-networks/

🔗 Best Practices for Preparing and Augmenting Image Data for Convolutional Neural Networks
It is challenging to know how to best prepare image data when training a convolutional neural network. This involves both scaling the pixel values and use of augmentation techniques during both the training and evaluation of the model. Instead of testing a wide range of options, a useful shortcut is to consider the types of …

🎥 Python Neural Networks - TensorFlow 2.0 Tutorial - What is a Neural Network?
👁 1 раз ⏳ 1629 сек.
This python neural network tutorial series will discuss how to use tensorflow 2.0 and provide tutorials on how to create neural networks with python and tensorflow. This specific video is the introduction video in the series and discusses what a neural network is.

Want a sneak peak into my life? Follow my Instagram @tech_with_tim where I'm going to be filming a video each morning sharing my goals for the day and what I have planned:
https://www.instagram.com/tech_with_tim

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​Announcing Google-Landmarks-v2: An Improved Dataset for Landmark Recognition & Retrieval
http://ai.googleblog.com/2019/05/announcing-google-landmarks-v2-improved.html/

🔗 Announcing Google-Landmarks-v2: An Improved Dataset for Landmark Recognition & Retrieval
Posted by Bingyi Cao and Tobias Weyand, Software Engineers, Google AI Last year we released Google-Landmarks , the largest world-wide la...

​Using What-If Tool to investigate Machine Learning models.

🔗 Using What-If Tool to investigate Machine Learning models.
An open source tool from Google to easily analyze ML models without the need to code.

​Joining Data Sources

🔗 Joining Data Sources
a must-have skill for data science

​Reinforcement Learning for Real-World Robotics

🔗 Reinforcement Learning for Real-World Robotics
Ideas from the literature on RL for real-world robot control

​A library for real-time video stream decoding to CUDA memory

By Constanta: https://github.com/Fonbet/argus-tensor-stream

🔗 Fonbet/argus-tensor-stream
A library for real-time video stream decoding to CUDA memory - Fonbet/argus-tensor-stream

🎥 Deep Learning with PyTorch - Intermediate Workshop
👁 4 раз ⏳ 10562 сек.
https://www.meetup.com/dsnet-blr/events/260996023/

Code:
- https://jvn.io/aakashns/a1b40b04f5174a18bd05b17e3dffb0f0
- https://jvn.io/aakashns/fdaae0bf32cf4917a931ac415a5c31b0

​Machine Learning Classification: The Success of Kickstarter Tech Projects

🔗 Machine Learning Classification: The Success of Kickstarter Tech Projects
As of April 2019, over 400,000 projects have been launched on Kickstarter. With crowdfunding becoming an ever-increasingly popular method…

🎥 OpenCV Python Tutorial For Beginners 16 - matplotlib with OpenCV
👁 1 раз ⏳ 889 сек.
In this video on OpenCV Python Tutorial For Beginners, I am going to show How to use matplotlib with OpenCV. matplotlib is a User friendly, but powerful, plotting library for python. I is commonly used with OpenCv images. pylab is a module in matplotlib that gets installed alongside matplotlib; and matplotlib.pyplot is a module in matplotlib. matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats.

Gist of code I used in this video (How to Disp

🎥 Нейросеть Вконтакте. Интервью с Разработчиком-Исследователем
👁 2 раз ⏳ 1196 сек.
Курс "React.js. Разработка веб-приложений":
https://vk.cc/9lSCcQ

В этом выпуске Loftblog в гостях у самой известной соцсети в России #ВКонтакте. Данил Гаврилов - разработчик из команды прикладных исследований расскажет нам про технологии искусственного интеллекта и их использовании.

Команда прикладных исследований ВКонтакте разработала нейросеть, которая генерирует новостные заголовки на русском и английском языках, cообщает пресс-служба соц.сети.

Ссылка на новость:
https://vk.cc/9l9Wp2

Полезные ссы

​https://m.youtube.com/watch?v=Wxb0jN0X7cs

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​Data Driven Growth with Python 🚀 — Part 1: Know Your Metrics

🔗 Data Driven Growth with Python 🚀 — Part 1: Know Your Metrics
Learn what and how to track with Python

​Наш телеграм канал - tglink.me/ai_machinelearning_big_data

https://towardsdatascience.com/6-bits-of-advice-for-data-scientists-6e5758c52fb2?source=collection_home---4------3---------------------

🔗 6 bits of advice for Data Scientists
Syndromes, Hypotheses, Fallacies, Lies, Awareness, and Probabilities

​Optimal Control: LQR

🔗 Optimal Control: LQR
Intuitive ground-up explanation to LQR, a fundamental concept in optimal control.