​Домашний кластер на Dask

🔗 Домашний кластер на Dask
Я недавно проводил исследование, в рамках которого было необходимо обработать несколько сотен тысяч наборов входных данных. Для каждого набора — провести некото...

🎥 TensorFlow 2.0 Tutorial - Part 1 | Introduction To TensorFlow 2.0 | TensorFlow Training | Edureka
👁 1 раз ⏳ 1275 сек.
🔥Edureka TensorFlow Training: https://www.edureka.co/ai-deep-learning-with-tensorflow
This Edureka TensorFlow 2.0 Tutorial - Part 1 ( Part 2 - https://youtu.be/H-L59o4SfxE ) covers the basics of TensorFlow with various new features and applications with respect to AI and Deep Learning. Below are the topics covered in this TensorFlow tutorial:
AI, ML & Deep Learning
Introduction To TensorFlow
What's New in TensorFlow 2.0?
Why TensorFlow?
Applications Of TensorFlow

🔹Check our complete Deep Learning With Te

https://youtu.be/7wsURXJrq7U
Paper: https://ieeexplore.ieee.org/abstract/document/8990014

🎥 ICRA2020 Baimukashev Optical Tactile Sensor
👁 1 раз ⏳ 93 сек.
Submitted to RA-L with ICRA2020 option

​How to Create the Simplest AI Using Neural Networks

🔗 How to Create the Simplest AI Using Neural Networks
Develop simple artificial intelligence creating a neural network model using Keras and input CSV file

​Building + deploying a Neural Style Transfer app with pre-trained models

🔗 Building + deploying a Neural Style Transfer app with pre-trained models
With Flask, Python3, OpenCV, Heroku (and a bunch of other stuff)

🎥 TensorFlow.js: Machine Learning in JavaScript by Jason Mayes
👁 1 раз ⏳ 2614 сек.
An event hosted in association with TensorFlow User Group Mysuru.

Talk Abstract
TensorFlow. js is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. Develop ML in the Browser. Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.

Join us for a short introductory talk to learn more about machine learning in JavaScript and some of the superpowers you gain by usin

🎥 Build a Probabilistic Classification using Scikit-learn | Machine Learning Tutorials | Codegnan
👁 1 раз ⏳ 5075 сек.
In this video you'll learn how to build a probabilistic classification using Machine Learning library SciKit-Learn. Basically Probability means it is the ratio of total number of outcomes and favorable number of outcomes. Watch the full video to get deep understanding on how probability relates to Machine Learning and how you can build one using sci-kit learn and also working on text and simple data set

Master Machine Learning Online/Classroom with Hewlett Packard Certification
Visit our Website here: http

🎥 Artificial Intelligence with a focus on Deep Learning - Today’s in-demand Skillset - Session 12
👁 1 раз ⏳ 6618 сек.
Start your Artificial Intelligence and Machine Learning journey by joining “Deep Learning and its applications : Beginners to Advance” course. The program builds a solid foundation from basics to advance by covering the most popular and widely used deep learning technologies and its applications.

Interactive learning: that’s what we do, and we’d like to share that with you. Come explore your learning journey with us!

For any support ,Please write us @ support@infyni.com, we will revert back within 48 Hou

​PyRetri: An Open-Source Deep Learning Based Unsupervised Image Retrieval Library Built on PyTorch
Paper: https://arxiv.org/abs/2005.02154
Github: https://github.com/PyRetri/PyRetri

🔗 PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Netwo
Despite significant progress of applying deep learning methods to the field of content-based image retrieval, there has not been a software library that covers these methods in a unified manner. In order to fill this gap, we introduce PyRetri, an open source library for deep learning based unsupervised image retrieval. The library encapsulates the retrieval process in several stages and provides functionality that covers various prominent methods for each stage. The idea underlying its design is to provide a unified platform for deep learning based image retrieval research, with high usability and extensibility. To the best of our knowledge, this is the first open-source library for unsupervised image retrieval by deep learning.

​Advances in Financial Machine Learning

Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Открыть в Telegram



📝 Advances_in_Financial_Machine_Learning_by_Marcos_Lopez_de_Prado.pdf - 💾8 893 995

​PyRetri: An open source deep learning based unsupervised image retrieval toolbox built on PyTorch🔥
Content-based Image retrieval

Paper: https://arxiv.org/abs/2005.02154

Github: https://github.com/PyRetri/PyRetri

Installation: https://github.com/PyRetri/PyRetri/blob/master/docs/INSTALL.md
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Netwo
Despite significant progress of applying deep learning methods to the field of content-based image retrieval, there has not been a software library that covers these methods in a unified manner. In order to fill this gap, we introduce PyRetri, an open source library for deep learning based unsupervised image retrieval. The library encapsulates the retrieval process in several stages and provides functionality that covers various prominent methods for each stage. The idea underlying its design is to provide a unified platform for deep learning based image retrieval research, with high usability and extensibility. To the best of our knowledge, this is the first open-source library for unsupervised image retrieval by deep learning.

​How to build a neural network to fill the missing part of a handwritten digit using GANs [Tutorial]

🔗 How to build a neural network to fill the missing part of a handwritten digit using GANs [Tutorial]
In this tutorial, we will get a clear overview of using Generative Adversarial Networks to build a neural network that will solve the problem of regenerating missing parts/regions of handwritten digits.

Всем привет, решил писать статьи, в частности обзоры на всякие машины, и это моя первая статья, если понравилось ставьте лайк на статье.
Первый обзор на BMW X3M, прочитай тебе обязательно понравится. Ссылка на статью у меня на стене.(не спам, не обман)

​AutoScale: инструмент Facebook сам решает, где запускать нейросеть — в телефоне или в облаке

🔗 AutoScale: инструмент Facebook сам решает, где запускать нейросеть — в телефоне или в облаке
Исследователи из Facebook и Университета штата Аризона представили новый инструмент под названием AutoScale, который определяет, где запустить нейросеть — в смар...

​Кривая хайпа: какие IT-технологии сейчас на пике и на что останется стабильный спрос

🔗 Кривая хайпа: какие IT-технологии сейчас на пике и на что останется стабильный спрос
В 2017 году спрос на блокчейн-разработчиков рос вместе с курсом биткоина. Количество вакансий снизилось, когда рынок разочаровался в новой технологии. Вместе с п...

​great-expectations/great_expectations

🔗 great-expectations/great_expectations
Always know what to expect from your data. Contribute to great-expectations/great_expectations development by creating an account on GitHub.

​Перевод книги Эндрю Ына «Страсть к машинному обучению» Главы 49 и 50

🔗 Перевод книги Эндрю Ына «Страсть к машинному обучению» Главы 49 и 50
предыдущие главы 49. За и против сквозного обучения Продолжим рассматривать систему распознавания речи: Большинство элементов этого конвейера созданы без примен...

​Machine Learning with Python: Classification (complete tutorial)

🔗 Machine Learning with Python: Classification (complete tutorial)
Data Analysis & Visualization, Feature Engineering & Selection, Model Design & Testing, Evaluation & Explainability

​Training ML models directly from GitHub

🔗 Training ML models directly from GitHub
In this post, I’ll show you how you can train machine learning models directly from GitHub. I originally presented this workshop at GitHub…

​Hierarchical Reinforcement Learning

🔗 Hierarchical Reinforcement Learning
Have a grasp at how Hierarchical RL works, the most popular approaches used and how you can start implementing it today.