​Plug-and-play differential privacy for your tensorflow code

#GoogleAI has just released a new library for training machine learning models with (differential) privacy for training data.

where you would write tf.train.GradientDescentOptimizer
instead just swap in the DPGradientDescentOptimizer

Tutorial: https://github.com/tensorflow/privacy/blob/master/tutorials/mnist_dpsgd_tutorial.py
Link: https://github.com/tensorflow/privacy

#Privacy #tensorflow

🔗 tensorflow/privacy
Library for training machine learning models with privacy for training data - tensorflow/privacy

​Desnapify

Logical followup of #pix2pix project by Isola et al., based on on Keras implementation by Thibault de Boissiere allows to remove that kat/dog faces from #Snapchat photoes.

Github: https://github.com/ipsingh06/ml-desnapify
Mentioned #Keras repo: https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/pix2pix

#DL

🔗 ipsingh06/ml-desnapify
Contribute to ipsingh06/ml-desnapify development by creating an account on GitHub.

​Playing Pong using Reinforcement Learning

https://towardsdatascience.com/intro-to-reinforcement-learning-pong-92a94aa0f84d?source=collection_home---4------2---------------------

🔗 Playing Pong from pixels using Reinforcement Learning
A gentle introduction to the key principles of Reinforcement Learning

​1. Теория вероятностей и математическая статистика
Год: 2013
Автор: Семенов В.А.

2. Теория вероятностей и математическая статистика
Год издания: 2012
Автор: Турчин В.Н.

3. Теория вероятностей и математическая статистика (2-е изд.)
Год: 2010
Автор: Балдин К.В., Башлыков В.Н., Рукосуев А.В.

4. Курс теории вероятностей
Год: 2005
Автор: Гнеденко Б.В.

5. Теория вероятностей и математическая статистика
Год выпуска: 2004
Автор: Н. Ш. Кремер
https://pp.userapi.com/c852024/v852024288/85e60/opCLhhJIy7w.jpg

📝 Семенов В.А. - Теория вероятностей и математическая статистика (Учебное пособие) - 2013.pdf - 💾10 459 973

📝 Турчин В.Н. - Теория вероятностей и математическая статистика - 2012.djvu - 💾1 583 149

📝 Балдин К.В., Башлыков В.Н., Рукосуев А.В. - Теория вероятностей и математическая статистика - 2010.pdf - 💾11 360 360

📝 Гнеденко Б.В. - Курс теории вероятностей (Классический университетский учебник) - 2005.djvu - 💾4 456 874

📝 Кремер Н.Ш. Теория вероятностей и математическая статистика.djvu - 💾6 641 712

🎥 Project Hydrogen: State of the Art Deep Learning on Apache Spark - Singapore Spark+AI Meetup
👁 1 раз ⏳ 2820 сек.
Speaker: Arseny Chernov

Event Page: https://www.meetup.com/Spark-Singapore/events/257581235/

Produced by Engineers.SG
Recorded by Ambrose Chua

Playing Pong using Reinforcement Learning
https://towardsdatascience.com/intro-to-reinforcement-learning-pong-92a94aa0f84d?source=collection_home---4------2---------------------

​Project Hydrogen: State of the Art Deep Learning on Apache Spark - Singapore Spark+AI Meetup

🔗 Project Hydrogen: State of the Art Deep Learning on Apache Spark - Singapore Spark+AI Meetup
Speaker: Arseny Chernov Event Page: https://www.meetup.com/Spark-Singapore/events/257581235/ Produced by Engineers.SG

https://habr.com/post/435924/

Нейросеть генерирует изображения блюд по рецептам их приготовления

#machinelearning #neuralnets #deeplearning #машинноеобучение

Наш телеграмм канал - https://t.me/ai_machinelearning_big_data

Tensorflow Machine Learning for Art and Music

🎥 Tensorflow Machine Learning for Art and Music
👁 1 раз ⏳ 585 сек.
In this video, I’ll share some of my favorite Tensorflow Magenta projects. The purpose of this video is to give you some ideas about how to learn Tensorflow and Machine Learning. If music or art inspire you to create, these are some great projects to get started.

I also share a visualization tool playground. This will help you better understand neural network in Tensorflow.

Here are the links to the projects
Visualize Neural Network - https://playground.tensorflow.org/
Tenserflow Magena Projects - https

Machine learning @ booking.com

🎥 Machine learning @ booking.com / Виктор Билык (booking.com)
👁 1 раз ⏳ 2634 сек.
HighLoad++ Siberia 2018

Зал «Красноярск», 25 июня, 16:00

Тезисы и презентация:
http://www.highload.ru/siberia/2018/abstracts/3608

В booking.com я занимаюсь созданием платформы для вывода в промышленную эксплуатацию продуктов машинного обучения.
Я расскажу о том, как устроена продуктовая разработка в booking.com и о месте машинного обучения в этом процессе. Покажу конкретные примеры применения моделей, расскажу о проблемах мониторинга их качественных характеристик и об архитектуре нашей (постоянно эволюц

​Investigating octopus camouflage with ICA and hierarchical clustering

https://towardsdatascience.com/investigating-octopus-camouflage-with-ica-and-hierarchical-clustering-df0e9a4ffaf4?source=collection_home---2------0---------------------

🔗 Investigating octopus camouflage with ICA and hierarchical clustering
How neuroscientists study this amazing skill with machine learning algorithms

​Interpreting the coefficients of linear regression

https://towardsdatascience.com/interpreting-the-coefficients-of-linear-regression-cc31d4c6f235?source=collection_home---4------4---------------------

🔗 Interpreting the coefficients of linear regression – Towards Data Science
Including transformations of variables

Playing Pong using Reinforcement Learning
https://towardsdatascience.com/intro-to-reinforcement-learning-pong-92a94aa0f84d?source=collection_home---4------2---------------------

Learning on non-Euclidean domains | Deep Learning on Computational Accelerators

🎥 Lecture 11 - Learning on non-Euclidean domains | Deep Learning on Computational Accelerators
👁 1 раз ⏳ 7687 сек.
Given by Prof. Alex Bronstein

https://habr.com/post/435984/

Нейросети и философия языка

#machinelearning #neuralnets #deeplearning #машинноеобучение

Наш телеграмм канал - https://t.me/ai_machinelearning_big_data