​10 Deep Learning Best Practices To Remember in 2020

🔗 10 Deep Learning Best Practices To Remember in 2020
As projects move from small-scale research to large-scale deployment, there are some universal best practices to achieve successful deep learning model rollout for a company of any size and means.

​AI, Brain Augmentation And Our Identities

🔗 AI, Brain Augmentation And Our Identities
Do you know who you are? If so, do you direct your own actions? These are two questions that we ask ourselves when someone asks us about…

🎥 DSC Webinar Series: Combining Human Intelligence with Machine Learning for NLP and Speech
👁 1 раз ⏳ 3585 сек.
Executing successful Natural Language Processing (NLP) and Speech projects in the real world is complicated. It is often difficult to find the right volume of raw data to annotate, especially if some categories/words/topics are very rare in the data. It is also difficult to find and manage the right people to annotate, transcribe or create the data, especially when the use case requires domain expertise or certain languages and accents.

Join this latest Data Science Central webinar and learn how to incorpo

🎥 Private AI Bootcamp Brainstorming Session + Q&A
👁 1 раз ⏳ 1032 сек.
The Private AI Bootcamp offered by Microsoft Research (MSR) focused on tutorials of building privacy-preserving machine learning services and applications with homomorphic encryption (HE). Around 30 PhD students were invited to gather at the Microsoft Research Lab in Redmond on Dec 2nd – 4th, 2019. The program contents were specifically designed for training. Participants mastered the use of HE, the Microsoft SEAL library, and the methodology behind building privacy-preserving machine learning solutions. As

​DeOldify: GAN based Image Colorization

🔗 DeOldify: GAN based Image Colorization
Bringing back the missing colors…

🎥 Private AI Bootcamp: Techniques in PPML
👁 1 раз ⏳ 3782 сек.
The Private AI Bootcamp offered by Microsoft Research (MSR) focused on tutorials of building privacy-preserving machine learning services and applications with homomorphic encryption (HE). Around 30 PhD students were invited to gather at the Microsoft Research Lab in Redmond on Dec 2nd – 4th, 2019. The program contents were specifically designed for training. Participants mastered the use of HE, the Microsoft SEAL library, and the methodology behind building privacy-preserving machine learning solutions. As

​Обзор Keras для TensorFlow

Перевод обзорного руководства с сайта Tensorflow.org. Это руководство даст вам основы для начала работы с Keras. Чтение займет 10 минут.

🔗 Обзор Keras для TensorFlow
Перевод обзорного руководства с сайта Tensorflow.org. Это руководство даст вам основы для начала работы с Keras. Чтение займет 10 минут. Импортируйте tf.ker...

​Three Practical Ways to Scale Machine Learning in the Real World

🔗 Three Practical Ways to Scale Machine Learning in the Real World
As NeurIPS sent the AI world a sobering message, the robotics industry seems to have a more pragmatic take on scaling machine learning…

​Как сделать свой автоскейлер для кластера
Привет! Мы обучаем людей работе с большими данными. Невозможно себе представить образовательную программу по большим данным без своего кластера, на котором все участники совместно работают. По этой причине на нашей программе он всегда есть :) Мы занимаемся его настройкой, тюнингом и администрированием, а ребята непосредственно запускают там MapReduce-джобы и пользуются Spark'ом.
В этом посте мы расскажем, как мы решали проблему неравномерной загрузки кластера, написав свой автоскейлер, используя облако Mail.ru Cloud Solutions.

🔗 Как сделать свой автоскейлер для кластера
Привет! Мы обучаем людей работе с большими данными. Невозможно себе представить образовательную программу по большим данным без своего кластера, на котором все у...

​Джедайская техника уменьшения сверточных сетей — pruning

Перед тобой снова задача детектирования объектов. Приоритет — скорость работы при приемлемой точности. Берешь архитектуру YOLOv3 и дообучаешь. Точность(mAp75) больше 0.95. Но скорость прогона всё еще низкая. Черт.
Сегодня обойдём стороной квантизацию. А под катом рассмотрим Model Pruning — обрезание избыточных частей сети для ускорения Inference без потери точности. Наглядно — откуда, сколько и как можно вырезать. Разберем, как сделать это вручную и где можно автоматизировать. В конце — репозиторий на keras.

🔗 Джедайская техника уменьшения сверточных сетей — pruning
Перед тобой снова задача детектирования объектов. Приоритет — скорость работы при приемлемой точности. Берешь архитектуру YOLOv3 и дообучаешь. Точность(mAp75) б...

​PyTorch/TPU MNIST Demo
https://colab.research.google.com/drive/1mxhxqg1rQEFwcEAqjtKZLzwtFlQaO44V#scrollTo=Afwo4H7kSd8P

🔗 Google Colaboratory

​Можно ли применять искусственный интеллект для приема на работу и расчета заработной платы?

https://bigdata-madesimple.com/artificial-intelligence-in-hr-and-payroll-embracing-disruption/

🔗 Artificial intelligence in HR and Payroll: Disruptions in human resources
Artificial intelligence applications are developing rapidly – and businesses are waking up to the potential of the technology in HR and payroll.

​Rachael's Farewell Stream | Kaggle

🔗 Rachael's Farewell Stream | Kaggle
Rachael will be leaving Kaggle for new opportunities in the new year, so please join her for her final live stream on the Kaggle channel where she'll go over some of her favorite notebooks from her time here. About Kaggle: Kaggle is the world's largest community of data scientists. Join us to compete, collaborate, learn, and do your data science work. Kaggle's platform is the fastest way to get started on a new data science project. Spin up a Jupyter notebook with a single click. Build with our huge reposi

​Optimized Deep Q-learning for Automated Atari Space Invaders: An Implementation in Tensorflow 2.0.

🔗 Optimized Deep Q-learning for Automated Atari Space Invaders: An Implementation in Tensorflow 2.0.
Exploring the Importance of Data Preprocessing

​The future of Machine Learning

🔗 The future of Machine Learning
A look into the future of ML with Jeff Dean

​Why is Python Programming a perfect fit for Big Data?

🔗 Why is Python Programming a perfect fit for Big Data?
We’ll discuss in the blog the major benefits of using Python for big data.

🎥 Machine Learning: A New Approach to Drug Discovery with Daphne Koller - #332
👁 1 раз ⏳ 2621 сек.
Today we continue our 2019 NeurIPS coverage joined by Daphne Koller, co-Founder and former co-CEO of Coursera and Founder and CEO of Insitro. We caught up with Daphne to discuss:

Her background in machine learning, beginning in ‘93, and her work with the Stanford online machine learning courses, and eventually her work at Coursera. The current landscape of pharmaceutical drug discovery, including the current pricing of drugs and misnomers with why drugs are so expensive, Her work at Insitro, a compan

​One of the best Machine Learning Professors
Full series on ML by CalTech Prof. Yaser Abu-Mostafa
https://www.youtube.com/watch?v=idu8kaPFf1A&list=PL41qI9AD63BMXtmes0upOcPA5psKqVkgS

🔗 CalTech ML Course Lecture 01 - The Learning Problem
The Learning Problem - Introduction; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lecture 1 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials on the course website - http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommo