Анализ рынка недвижимости методом случайного леса
https://habrahabr.ru/post/329504/
https://habrahabr.ru/post/329504/
habrahabr.ru
Анализ рынка недвижимости методом случайного леса
Решалась задача анализа текущих предложений на минском рынке недвижимости с целью поиска недооцененных квартир. В качестве источника информации был выбран сайт...
cs231n lecture from Stanford, comparing between TensorFlow and PyTorch
http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture8.pdf
http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture8.pdf
Hybrid Generative-Discriminative Deep Models
http://www.openias.org/hybrid-generative-discriminative
http://www.openias.org/hybrid-generative-discriminative
www.openias.org
OpenIAS | Hybrid Generative-Discriminative Deep Models
Deep discriminative classifiers perform remarkably well on problems witha lot of labeled data. So-called deep generative models tend to excel whenlabeled tra...
PyTorch Tutorial for Deep Learning Researchers
https://github.com/yunjey/pytorch-tutorial
https://github.com/yunjey/pytorch-tutorial
GitHub
GitHub - yunjey/pytorch-tutorial: PyTorch Tutorial for Deep Learning Researchers
PyTorch Tutorial for Deep Learning Researchers. Contribute to yunjey/pytorch-tutorial development by creating an account on GitHub.
Unsupervised Machine Learning for Fun & Profit with Basket Clusters
https://medium.com/@gaetanconsulting/unsupervised-machine-learning-for-fun-profit-with-basket-clusters-17a1161e7aa1
https://medium.com/@gaetanconsulting/unsupervised-machine-learning-for-fun-profit-with-basket-clusters-17a1161e7aa1
Hacker Noon
Unsupervised Machine Learning for Fun & Profit with Basket Clusters
I finally beat the S&P 500 by 10%. This might not sound like much but when we’re dealing with large amounts of capital and with good…
Нейронные сети в детектировании номеров
https://habrahabr.ru/company/recognitor/blog/329636/
https://habrahabr.ru/company/recognitor/blog/329636/
Habr
Нейронные сети в детектировании номеров
Распознавание автомобильных номеров до сих пор является самым продаваемым решением на основе компьютерного зрения. Сотни, если не тысячи продуктов конкурируют на этом рынке уже на протяжении 20-25...
Understanding Tensorflow using Go
https://pgaleone.eu/tensorflow/go/2017/05/29/understanding-tensorflow-using-go/
https://pgaleone.eu/tensorflow/go/2017/05/29/understanding-tensorflow-using-go/
P. Galeone's blog
Understanding Tensorflow using Go
Tensorflow is not a Machine Learning specific library, instead, is a general purpose computation library that represents computations with graphs. Its core is implemented in C++ and there are also bindings for different languages. The bindings for the Go…
An Overview of Multi-Task Learning in Deep Neural Networks
http://sebastianruder.com/multi-task/
http://sebastianruder.com/multi-task/
Sebastian Ruder
An Overview of Multi-Task Learning for Deep Learning
This blog post gives an overview of multi-task learning in deep neural networks. It discusses existing approaches as well as recent advances.
How Bayesian inference works
https://brohrer.github.io/how_bayesian_inference_works.html
https://brohrer.github.io/how_bayesian_inference_works.html
Introduction to Probabilistic Modelling and Machine Learning
https://www.youtube.com/watch?v=5KdWhDpeQvU&index=1&list=PLAbhVprf4VPlqc8IoCi7Qk0YQ5cPQz9fn
https://www.youtube.com/watch?v=5KdWhDpeQvU&index=1&list=PLAbhVprf4VPlqc8IoCi7Qk0YQ5cPQz9fn
YouTube
Lecture 1 (part 1): Introduction to Probabilistic Modelling and Machine Learning
Machine Learning and Nonparametric Bayesian Statistics by prof. Zoubin Ghahramani. These lectures are part of the Visiting Professor Programme co-financed by...
Новый корпус русского языка: почищенный, дедуплицированный и автоматически размеченный UD 2.0, в основном из common crawl (архив 24 Гб)
https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-1989
https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-1989
A TensorFlow Implementation of Machine Translation In Neural Machine Translation in Linear Time
https://github.com/Kyubyong/bytenet_translation
https://github.com/Kyubyong/bytenet_translation
GitHub
Kyubyong/bytenet_translation
bytenet_translation - A TensorFlow Implementation of Machine Translation In Neural Machine Translation in Linear Time
A Tour of PyTorch Internals (Part I)
https://gist.github.com/killeent/4675635b40b61a45cac2f95a285ce3c0
https://gist.github.com/killeent/4675635b40b61a45cac2f95a285ce3c0
Gist
internals.md
GitHub Gist: instantly share code, notes, and snippets.
Automate your Machine Learning in Python – TPOT and Genetic Algorithms
https://blog.alookanalytics.com/2017/05/25/automate-your-machine-learning/
https://blog.alookanalytics.com/2017/05/25/automate-your-machine-learning/
alookanalytics blog
Automate your Machine Learning in Python – TPOT and Genetic Algorithms
Automatic Machine Learning (AML) is a pipeline, which enables you to automate the repetitive steps in your Machine Learning (ML) problems and so save time to focus on parts where your expertise has…
Polyaxon: A platform and a deep Learning library for TensorFlow
https://github.com/polyaxon/polyaxon
https://github.com/polyaxon/polyaxon
GitHub
GitHub - polyaxon/polyaxon: MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle - polyaxon/polyaxon
How to Evaluate the Skill of Deep Learning Models
http://machinelearningmastery.com/evaluate-skill-deep-learning-models/
http://machinelearningmastery.com/evaluate-skill-deep-learning-models/
MachineLearningMastery.com
How to Evaluate the Skill of Deep Learning Models - MachineLearningMastery.com
I often see practitioners expressing confusion about how to evaluate a deep learning model. This is often obvious from questions like: What random seed should I use? Do I need a random seed? Why don't I get the same results on subsequent runs? In this post…
Легкое погружение в TensorFlow на примерах популярных алгоритмов машинного обучения https://github.com/aymericdamien/TensorFlow-Examples
GitHub
GitHub - aymericdamien/TensorFlow-Examples: TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) - aymericdamien/TensorFlow-Examples
Babble-rnn: Generating speech from speech with LSTM networks
http://babble-rnn.consected.com/docs/babble-rnn-generating-speech-from-speech-post.html
http://babble-rnn.consected.com/docs/babble-rnn-generating-speech-from-speech-post.html
DeepMind describes changes in newer version of AlphaGo
https://www.theverge.com/2017/5/30/15712300/alphago-ai-humanity-google-artificial-intelligence-ke-jie
https://www.theverge.com/2017/5/30/15712300/alphago-ai-humanity-google-artificial-intelligence-ke-jie
The Verge
AI, the humanity!
AlphaGo’s victory isn’t a defeat for humans — it’s an opportunity
pix2code: Generating Code from a Graphical User Interface Screenshot
https://uizard.io/research#pix2code
https://uizard.io/research#pix2code