Automate workflows and deliver smooth user experiences with Django and Celery Link

How to quickly get a handle on almost any tabular dataset Link

Integromat lets you connect apps and automate workflows in a few clicks. Move data between apps without effort so you can focus on growing your business. Link

Jupyter Notebook is probably the most popular tool used by Data Scientists. It allows mixing code, text, and inspecting the output in one document. This is something that is not possible with some other programming IDEs. However, the vanilla version of the Jupyter notebooks is not perfect. In this article, we will show you how to make it slightly better by installing some useful extensions. Link

The Python itertools library is provides extremely useful utility functions for dealing with iterables. By becoming fluent in the itertools functions, you can combine them in new ways and use them as building blocks for tackling complex problems in very few lines of code. In this article, you will see 7 practical examples of the applications of itertools functions. Link

A python library for decision tree visualization and model interpretation. Currently supports scikit-learn, XGBoost, Spark MLlib, and LightGBM trees. Link

Developers and Open Source authors now have a massive amount of services offering free tiers, but it can be hard to find them all to make informed decisions. This is a list of software (SaaS, PaaS, IaaS, etc.) and other offerings that have free tiers for developers. The scope of this particular list is limited to things that infrastructure developers (System Administrator, DevOps Practitioners, etc.) are likely to find useful. We love all the free services out there, but it would be good to keep it on topic.

Molecular Biophysics - all lectures and concepts Link

Human-readable, visual reports for every ML pipeline Link

This best-practices article intends for developers interested in creating RESTful Web services that provide high reliability and consistency across multiple service suites; following these guidelines; services are positioned for rapid, widespread, public adoption by internal and external clients. Link

Pypeln (pronounced as “pypeline”) is a simple yet powerful Python library for creating concurrent data pipelines. Link

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This article will create a new VPC and the necessary resources to stand up a Redshift cluster in the new VPC. That way, we can blow this all away without affecting the state of our environment pre-tutorial. Link