Tips to prepare an outstanding CV for data science roles
https://www.analyticsvidhya.com/blog/2014/11/tips-prepare-cv-data-science-roles/

Weak Supervision: A New Programming Paradigm for Machine Learning:
http://ai.stanford.edu/blog/weak-supervision/

23 марта в офисе mail.ru проводится бесплатная конференция по машинному обучению.
С докладами выступят программисты Почты Mail.ru и разработчики направлений машинного обучения.

Подробную информацию можно узнать по адресу: https://vk.cc/99ejkv

How to Clean Your Data Quickly in 5 Steps:
https://www.chi2innovations.com/blog/discover-data-blog-series/how-clean-your-data-quickly-5-steps/

A neural data science: how and why.The rough guide to doing data science on neurons
https://medium.com/the-spike/a-neural-data-science-how-and-why-d7e3969086f2

A Simple Guide to Semantic Segmentation.
A comprehensive review of Classical and Deep Learning methods for Semantic Segmentation
https://medium.com/beyondminds/a-simple-guide-to-semantic-segmentation-effcf83e7e54?sk=3d1a5a32a19d611fbd81028cfd4f23fd

Learnability can be undecidable
https://www.nature.com/articles/s42256-018-0002-3.pdf

DevDocs combines multiple developer documentations in a clean and organized web UI with instant search, offline support, mobile version, dark theme, keyboard shortcuts, and more.

https://devdocs.io/

Open-sourcing PyTorch-BigGraph for faster embeddings of extremely large graphs
Facebook выложил эмбеддинги Wikidata + PyTorch-расширение.

https://ai.facebook.com/blog/open-sourcing-pytorch-biggraph-for-faster-embeddings-of-extremely-large-graphs/

Серия постов о Docker for Machine Learning

https://mlinproduction.com/docker-for-ml-part-1/

Monorepo vs. polyrepo
#Git

https://github.com/joelparkerhenderson/monorepo_vs_polyrepo

An Introduction to Biomedical Image Analysis with TensorFlow and DLTK

https://medium.com/tensorflow/an-introduction-to-biomedical-image-analysis-with-tensorflow-and-dltk-2c25304e7c13

The javanoscript architecture-free neural network library for node.js and the browser

#NeuralNetworkJavaScript

http://caza.la/synaptic/#/

Neural networks in JavaScript
A fun and practical introduction to Brain.js. This course teaches you how to build neural networks in JavaScript through 19 interactive tutorials.

#NeuralNetworkJavaScript
https://scrimba.com/g/gneuralnetworks

Brainy: A simple PHP class for Machine Learning

#PHPMachineLearning

https://www.danielefavi.com/brainy-a-simple-php-class-for-machine-learning/

PHP-ML - Machine Learning library for PHP

#PHPMachineLearning

https://php-ml.readthedocs.io/en/latest/

FANN (Fast Artificial Neural Network)

#PHPMachineLearning
https://www.php.net/manual/en/book.fann.php

Pyodide: Bringing the scientific Python stack to the browser
https://hacks.mozilla.org/2019/04/pyodide-bringing-the-scientific-python-stack-to-the-browser/

Computational and Inferential Thinking.
The Foundations of Data Science.
By Ani Adhikari and John DeNero

https://www.inferentialthinking.com/chapters/intro

Pandas for Geospatial data:

🐼Working with coordinates can be a nightmare and GeoPandas tool comes quite handy.

The goal of GeoPandas is to make working with geospatial data in python easier. It combines the capabilities of pandas and shapely, providing geospatial operations in pandas and a high-level interface to multiple geometries to shapely. GeoPandas enables you to easily do operations in python that would otherwise require a spatial database such as PostGIS.

🌎 Learn more here: http://geopandas.org/

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xoxo