​Изучение поведения пользователей интернет – магазина. Часть 1

🔗 Изучение поведения пользователей интернет – магазина. Часть 1
Введение Из всего многообразия задач, я, будучи только приступившим к работе в офисе, выбрал исследования поведения пользователей на сайте магазина. Данных от п...

​PEGASUS: A State-of-the-Art Model for Abstractive Text Summarization">
PEGASUS: A State-of-the-Art Model for Abstractive Text Summarization

🔗 PEGASUS: A State-of-the-Art Model for Abstractive Text Summarization
Posted by Peter J. Liu and Yao Zhao, Software Engineers, Google Research Students are often tasked with reading a document and producing...

​COVID-19: Social Distancing Detector

🔗 COVID-19: Social Distancing Detector
Build a simple Social Distancing Detector to monitor the practice of social distancing in a crowd

​The Bayesian Paradigm & Ridge Regression

🔗 The Bayesian Paradigm & Ridge Regression
Is there a connection?

​How to Remove Racial Discrimination from Data Science

🔗 How to Remove Racial Discrimination from Data Science
On Finding and Fixing Latent Racial Bias

🎥 Machine Learning 101: Classification
👁 1 раз ⏳ 3992 сек.
Have you always been curious about what machine learning can do for your business problem, but could never find the time to learn the practical necessary skills? Do you wish to learn what Classification, Regression, Clustering and Feature Extraction techniques do, and how to apply them using the Oracle Machine Learning family of products?

Join us for this special series “Oracle Machine Learning Office Hours – Machine Learning 101”, where we will go through the main steps of solving a Business Problem from

🎥 ADL4CV - Graph Neural Networks and Attention
👁 1 раз ⏳ 5266 сек.
Advanced Deep Learning for Computer Vision
TUM Summer Semester 2020

Prof. Laura Leal-Taixé
Dynamic Vision and Learning Group
Technical University Munich

​How to Use StandardScaler and MinMaxScaler Transforms in Python - Machine Learning Mastery

🔗 How to Use StandardScaler and MinMaxScaler Transforms in Python - Machine Learning Mastery
Many machine learning algorithms perform better when numerical input variables are scaled to a standard range. This includes algorithms that use a weighted sum of the input, like linear regression, and algorithms that use distance measures, like k-nearest neighbors. The two most popular techniques for scaling numerical data prior to modeling are normalization and standardization. Normalization scales each input variable separately to

​5 видеороликов о пакете dplyr языка R

dplyr – популярный пакет для обработки данных в языке R. Небольшой плейлист из 10-15-минутных роликов познакомит с основным функциями пакета dplyr с учётом последних нововведений версии 1.0.0.

https://proglib.io/w/ef8137a6

🔗 5 видеороликов о пакете dplyr языка R
dplyr – популярный пакет для обработки данных в языке R. Небольшой плейлист из 10-15-минутных роликов познакомит с основным функциями пакета dplyr с учётом последних нововведений версии 1.0.0.

​5 free online courses from Harvard you can sign up for right now to learn how to code

https://www.businessinsider.com/free-harvard-courses-on-coding-programming-computer-science-2020-6

🔗 5 free online courses from Harvard you can sign up for right now to learn how to code
These self-paced classes teach everything from the basics of coding, to languages like Python and JavaScript.

​OCR-конвейер для обработки документов

🔗 OCR-конвейер для обработки документов
Сегодня я расскажу о том, как создавалась система для переноса текста из бумажных документов в электронную форму. Мы рассмотрим два основных этапа: выделение обл...

​Люди ломаются на логике, роботы — на всем понемногу. Экзамены по русскому для NLP-моделей

🔗 Люди ломаются на логике, роботы — на всем понемногу. Экзамены по русскому для NLP-моделей
Чтобы машины могли обрабатывать текст на русском и «понимать» его, в NLP используются универсальные языковые модели и трансформеры — BERT, RoBERTa, XLNet и други...

​Как мы взламывали «умную» фабрику

🔗 Как мы взламывали «умную» фабрику
Хотя процесс подключения предприятий к интернету давно уже носит массовый характер, с точки зрения кибербезопасности каждый такой случай уникален, и охватить вс...

​ultralytics/yolov5

🔗 ultralytics/yolov5
YOLOv5 in PyTorch ? ONNX ? CoreML ? iOS. Contribute to ultralytics/yolov5 development by creating an account on GitHub.

​London Bike Ride Forecasting with Graph Convolutional Networks

🔗 London Bike Ride Forecasting with Graph Convolutional Networks
End-to-End PyTorch Deep-Learning from Concept to Validation

​Neural Network Part1:Inside a single neuron

🔗 Neural Network Part1:Inside a single neuron
The perceptron or a single neuron is the fundamental building block of a neural network .The idea of a neuron is basic but essential .

🎥 Machine Learning - TensorFlow Extended com Apache Airflow
👁 1 раз ⏳ 5980 сек.
Link GitHub: https://github.com/AlvaroCavalcante/tensorflow-extended-tutorial

🎥 Machine Learning through Streaming at Lyft
👁 1 раз ⏳ 2462 сек.
Video with transcript included: https://bit.ly/2AVIBot

Sherin Thomas talks about the challenges of building and scaling a fully managed, self-service platform for stream processing using Flink, best practices, and common pitfalls. Thomas goes into the details of how the Lyft system evolved over the last couple of years, as well as the design tradeoffs they made.

This presentation was recorded at QCon London 2020: http://bit.ly/2VfRldq

#Flink #MachineLearning #Streaming

🎥 Deep Learning Text Recognition Using Programmatically Generated Synthetic Data
👁 1 раз ⏳ 1831 сек.
This presentation covers three important points 1) You can create a text recognition model for Urdu using Deep Learning. 2) You can create synthetic data for Urdu programmatically. 3) The deep learning model recognises synthetic data really well.

This was a presentation I did at BrumAI in November 2018.

🎥 01 DEEP LEARNING LES RESEAUX DE NEURONES
👁 1 раз ⏳ 2148 сек.
première vidéos sur le deep learning avec tensorflow


Code source : https://github.com/ilmare0506/DEEP-LEARNING
TensorFlow : https://www.tensorflow.org/