​Donald Knuth: Algorithms, Complexity, Life, and The Art of Computer Programming | AI Podcast

🔗 Donald Knuth: Algorithms, Complexity, Life, and The Art of Computer Programming | AI Podcast
Donald Knuth is one of the greatest and most impactful computer scientists and mathematicians ever. He is the recipient in 1974 of the Turing Award, considered the Nobel Prize of computing. He is the author of the multi-volume work, the magnum opus, The Art of Computer Programming. He made several key contributions to the rigorous analysis of the computational complexity of algorithms. He popularized asymptotic notation, that we all affectionately know as the big-O notation. He also created the TeX typesett

​Unbalanced data loading for multi-task learning in PyTorch

🔗 Unbalanced data loading for multi-task learning in PyTorch
Working on multi-task learning (MTL) problems require unique training setup, mainly in terms of data handling, model architecture, and…

​Calculating Catchment with Human Mobility Data

🔗 Calculating Catchment with Human Mobility Data
Leveraging Human Mobility Data to identify potential customers

​A Very Unlikely Chess Game

🔗 A Very Unlikely Chess Game
Almost 25 years after Kasparov vs. Deep Blue, another seminal man vs. machine matchup: Neither competitor has much to be proud of here. White has a poor opening. Black screws up and loses his queen…

🎥 Deep Learning for Higgs and New Physics Searches at the LHC
👁 1 раз ⏳ 3224 сек.
Professor Javier Duarte
2019 11 11
University of California, San Diego

Since the discovery of the Higgs boson at the Large Hadron Collider in 2012, developments in deep learning have expanded our ability to study the production of Higgs bosons and other particles with very large momenta. By studying these particles, we may be able to discover new physics at very high energy scales inaccessible directly at the LHC. I will explain these searches and talk about the direction that deep learning is taking in p

🎥 Deep Learning Formulas for NLP Applications | Chenglong Chen | Kaggle
👁 1 раз ⏳ 1633 сек.
Content note: Speaker is presenting in Mandarin but presentation and subtitles are in English.

Kaggle Days China edition was held on October 19-20 at Damei Center, Beijing.

More than 400 data scientists and enthusiasts gathered to learn, make friends, and compete in a full-day offline competition.

Kaggle Days is produced by LogicAI and Kaggle.

About LogicAI:
LogicAI is a boutique Data Science consultancy company owned by Kaggle fans and Grandmasters. As a global company, they do custom end-to-end AI and

​Использование Clickhouse в качестве замены ELK, Big Query и TimescaleDB
Clickhouse — это столбцовая система управления базами данных для онлайн обработки аналитических запросов (OLAP) с открытым исходным кодом, созданная Яндексом. Ее используют Яндекс, CloudFlare, VK.com, Badoo и другие сервисы по всему миру для хранения действительно больших объемов данных (вставка тысяч строк в секунду или петабайты данных, хранящихся на диске).

В обычной, «строковой» СУБД, примерами которых служат MySQL, Postgres, MS SQL Server, данные хранятся в таком порядке:

При этом значения, относящиеся к одной строке, физически хранятся рядом. В столбцовых СУБД значения из разных столбцов хранятся отдельно, а данные одного столбца – вместе:

🔗 Использование Clickhouse в качестве замены ELK, Big Query и TimescaleDB
Clickhouse — это столбцовая система управления базами данных для онлайн обработки аналитических запросов (OLAP) с открытым исходным кодом, созданная Яндексом. Ее...

​MuZero: DeepMind’s New AI Mastered More Than 50 Games

🔗 MuZero: DeepMind’s New AI Mastered More Than 50 Games
❤️ Check out Linode here and get $20 free credit on your account: https://www.linode.com/papers 📝 The paper "Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model" is available here: https://arxiv.org/abs/1911.08265 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Anthony Vdovitchenko, Benji Rabhan, Brian Gilman, Bryan Learn, Christian Ahlin, Claudio Fernandes, Daniel Hasegan, Dan Kennedy, Dennis

​Data project checklist

https://www.fast.ai//2020/01/07/data-questionnaire/

Designing great data products
The Drivetrain Approach: A four-step process for building data products.

https://www.oreilly.com/radar/drivetrain-approach-data-products/

🔗 Data project checklist
There's a lot more to creating useful data projects than just training an accurate model

​Как сделать бота, который превращает фото в комикс. Часть вторая. Обучение модели
⇨ Первая часть

И снова здравствуйте!

Как вы могли заметить, праздники несколько подкосили график выхода статей.
Думаю, многие за это время успели если не полностью обучить свою модель, то хотя бы поэкспериментировать с различными наборами данных.

1. Ставим дистрибутив
2. Качаем фотки
3. ???
4. Profit!

Если же вам было не до этих наших нейросетей, или вы начинаете чтение с этой статьи, то, как говорится, нет времени объяснять, берем дистрибутив, качаем нужные фотки, и поехали!

🔗 Как сделать бота, который превращает фото в комикс. Часть вторая. Обучение модели
⇨ Первая часть И снова здравствуйте! Как вы могли заметить, праздники несколько подкосили график выхода статей. Думаю, многие за это время успели если не полн...

🎥 Vahid Moosavi - 'Machine learning literacy for designers & engineers'
👁 1 раз ⏳ 3761 сек.
Dr Vahid Moosavi (Senior Researcher, CAAD, ETH)

Machine learning literacy for designers and engineers

Machine learning and data together offer a universal way of looking at the world phenomena, which is radically different than the classical expert-based disciplinary research. This new approach of computational modeling has inverted the classical notion of expertise from “having the answers to the known questions” to “learning to ask good questions”. This will have important consequences on the ways we th

​Автоматическое обновление кода до TensorFlow 2

В материале предоставлен перевод руководства по автоматическом обновлению кода с TensorFlow 1.x до Tensorflow 2 с помощью скрипта обновления tf_upgrade_v2.

🔗 Автоматическое обновление кода до TensorFlow 2
В материале предоставлен перевод руководства по автоматическом обновлению кода с TensorFlow 1.x до Tensorflow 2 с помощью скрипта обновления tf_upgrade_v2. Te...

​Best NLP Research of 2019 - Open Data Science Conference

🔗 Best NLP Research of 2019 - Open Data Science Conference
Natural language processing (NLP) is one of the most important technologies to arise in recent years. Specifically, 2019 has been a big year for NLP with the introduction of the revolutionary BERT language representation model. There are a large variety of underlying tasks and machine learning models powering NLP applications....

🎥 PyTorch: A Modern Library for Machine Learning
👁 1 раз ⏳ 3745 сек.
TITLE: PyTorch: A Modern Library for Machine Learning
SPEAKER: Adam Paszke
DATE: 12/16/19

ABSTRACT
The recent explosion in the power and popularity of machine learning techniques has been fueled in part by the ecosystem of open source Python libraries. One of those was PyTorch, a successor to Torch7, which is rapidly becoming one of the most essential tools in every ML researcher’s toolbox.

However, research is not the end of the story. Machine learning is transforming entire fields, meaning that efficien

​Herding cats, or how not to organise your data science team.

🔗 Herding cats, or how not to organise your data science team.
Different ways of organising your data science team bring different problems and opportunities,

​AEI: Artificial ‘Emotional’ Intelligence

https://towardsdatascience.com/aei-artificial-emotional-intelligence-ea3667d8ece

🔗 AEI: Artificial ‘Emotional’ Intelligence
It all began about 2,000 years ago when Plato wrote, “All learning has an emotional base.”

🎥 DataSphere: How to build an AI from zero to learn to play and solve a tough game by Juantomás García
👁 1 раз ⏳ 1984 сек.
AbadIA: How to build an AI from zero to learn to play and solve a tough game

The process of building an AI looks like it is so glamorous but is a long process, and at the end of the day, the tasks related to the AI model are just 5% or less of the project.
We will see how to start an AI project from zero: defining the objectives, creating the architecture, building the game interfaces, massive data pipelines, defining model strategies, how to parallelize everything, etc.
The “the abbey of crime” is an adam

🎥 Machine Learning vs Artificial Intelligence | AI vs ML | Intellipaat
👁 1 раз ⏳ 1316 сек.
🔥Intellipaat Artificial Intelligence Master's course: https://intellipaat.com/artificial-intelligence-masters-training-course/
In this Machine Learning vs Artificial Intelligence or ai vs ml video you will learn about the difference between ai and machine learning also known as ml vs ai.
#machinelearningvsartificialintelligence #aivsml #ai #intellipaat #machinelearning #intellipaat

📌 Do subscribe to Intellipaat channel & get regular updates on videos: http://bit.ly/Intellipaat

🔗 Watch AI video tutorials

​Machine Learning Web Application deployment in 5 steps

🔗 Machine Learning Web Application deployment in 5 steps
You’ve built a model and an application; now it’s time to let the world see! Learn to deploy an ML web application — for free — using AWS.

🎥 Causality, Independence, and Adaptive Prediction #ibmresearch
👁 1 раз ⏳ 4173 сек.
Causality, Independence, and Adaptive Prediction

This video is published under the license of Creative common (reused allow)
Publisher: IBM Research
Source: https://www.youtube.com/watch?v=AMr7RJ4pjAQ

Invited talk at First Workshop on Bridging Causal inference, Reinforcement learning, and Transfer learning (CRT 2019) https://crt2019.github.io/

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