python

1.Django + Vue + GraphQL + AWS Cookiecutter 2.Cookiecutter Pipeline for SAM based Serverless App 3.Cookiecutter Python Microservice 4.A cookiecutter template for bootstrapping a FastAPI and React project using a modern stack. 5.Cookiecutter for pyTorch 6.Cookiecutter for Data Science 1 7.Cookiecutter for Data Science 2 8.Cookiecutter for Data Science 3

This article is a comprehensive overview of a step-by-step guide to deploy a simple sentiment analysis application using streamlit and Docker Link

1.Cookiecutter Django 2.Jumpstart your Django Project with Cookiecutter 3.Using django cookiecutter cloud storage (GCP) 4.AWS Blue Green deployment 5.Cookiecutter Flask 6.Cookiecutter Django + PostGres + Docker + DramatiQ 7.Django + React 8.Django + React example 9.Django + React tutorial

Modin is an early-stage project at UC Berkeley’s RISELab designed to facilitate the use of distributed computing for Data Science. It is a multiprocess Dataframe library with an identical API to pandas that allows users to speed up their Pandas workflows. Link

Given about 7000 experimental datapoints, we want to understand which parameters influence the metric we want to optimize: valid ppl. How can HiPlot help? On the parallel plot, each line represents one datapoint. Slicing on the valid ppl axis reveals that higher values for lr lead to better models. We will focus on higher values for the lr then. Un-slice the valid ppl axis by clicking on the axis, but outside of the current slice.

Loguru is a library which aims to bring enjoyable logging in Python. Did you ever feel lazy about configuring a logger and used print() instead?… I did, yet logging is fundamental to every application and eases the process of debugging. Using Loguru you have no excuse not to use logging from the start, this is as simple as from loguru import logger. Also, this library is intended to make Python logging less painful by adding a bunch of useful functionalities that solve caveats of the standard loggers.