#30DaysOfStreamlit is a 30-day social challenge for you to build and deploy Streamlit apps.

Related tags

Machine Learning30days
Overview

30 Days Of Streamlit 🎈

This is the official repo of #30DaysOfStreamlit — a 30-day social challenge for you to learn, build and deploy Streamlit apps.

How to participate

All you need to participate is a computer, a basic understanding of Python, and your curiosity. 🧠

A new challenge is released daily via Streamlit's Twitter and LinkedIn accounts as well as the #30DaysOfStreamlit app.

Streamlit App

Complete the daily challenges, share your solutions with us on Twitter or LinkedIn, and get rewarded with cool Streamlit swag! 😎

What are the daily challenges?

Find out more about the specific challenges by participating! The 30-day challenges are divided by 3 levels of difficulty to appeal to participants of all skill levels:

Beginner (Days 1-7) Intermediate (Days 8-23) Advanced (Days 24-30)
Set up your local and cloud coding environments, install Streamlit, and build your first Streamlit app. Learn about a new Streamlit command each day and use it to create and deploy a simple Streamlit app. Learn about important topics such as session state, efficient data and memory management via caching, complex layouts, and much more.

Prizes

If getting up to speed with the fastest and easiest way to build data apps isn't already the best summer gift, you can also win Streamlit goodies!

Complete the daily challenges, share your solutions with us on Twitter or LinkedIn, and get rewarded with cool Streamlit swag! 🎁

Resources

Translations

Want to help us expand the reach of #30DaysOfStreamlit and English isn't your primary language? Translate the challenges into your preferred language and link to them below!

Owner
Streamlit
The fastest way to build custom ML tools
Streamlit
GitHub Repository https://share.streamlit.io/streamlit/30days/
Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Artsem Zhyvalkouski 64 Nov 30, 2022
TIANCHI Purchase Redemption Forecast Challenge

TIANCHI Purchase Redemption Forecast Challenge

Haorui HE 4 Aug 26, 2022
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Microsoft 241 Dec 26, 2022
2D fluid simulation implementation of Jos Stam paper on real-time fuild dynamics, including some suggested extensions.

Fluid Simulation Usage Download this repo and store it in your computer. Open a terminal and go to the root directory of this folder. Make sure you ha

Mariana Ávalos Arce 5 Dec 02, 2022
A Powerful Serverless Analysis Toolkit That Takes Trial And Error Out of Machine Learning Projects

KXY: A Seemless API to 10x The Productivity of Machine Learning Engineers Documentation https://www.kxy.ai/reference/ Installation From PyPi: pip inst

KXY Technologies, Inc. 35 Jan 02, 2023
Repository for DCA0305, an undergraduate course about Machine Learning Workflows and Pipelines

Federal University of Rio Grande do Norte Technology Center Department of Computer Engineering and Automation Machine Learning Based Systems Design Re

Ivanovitch Silva 81 Oct 18, 2022
LinearRegression2 Tvads and CarSales

LinearRegression2_Tvads_and_CarSales This project infers the insight that how the TV ads for cars and car Sales are being linked with each other. It i

Ashish Kumar Yadav 1 Dec 29, 2021
Coursera Machine Learning - Python code

Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen

Jordi Warmenhoven 859 Dec 10, 2022
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar

Facebook 15.4k Jan 07, 2023
A Tools that help Data Scientists and ML engineers train and deploy ML models.

Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers

Domino Data Lab 73 Oct 17, 2022
Course files for "Ocean/Atmosphere Time Series Analysis"

time-series This package contains all necessary files for the course Ocean/Atmosphere Time Series Analysis, an introduction to data and time series an

Jonathan Lilly 107 Nov 29, 2022
Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn

Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast

Tom Weichle 2 Apr 18, 2022
[HELP REQUESTED] Generalized Additive Models in Python

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

daniel servén 747 Jan 05, 2023
The Emergence of Individuality

The Emergence of Individuality

16 Jul 20, 2022
scikit-learn is a python module for machine learning built on top of numpy / scipy

About scikit-learn is a python module for machine learning built on top of numpy / scipy. The purpose of the scikit-learn-tutorial subproject is to le

Gael Varoquaux 122 Dec 12, 2022
Projeto: Machine Learning: Linguagens de Programacao 2004-2001

Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2

Victor Hugo Negrisoli 0 Jun 29, 2021
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

Jeong-Yoon Lee 720 Dec 25, 2022
A classification model capable of accurately predicting the price of secondhand cars

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this

Akarsh Singh 2 Sep 13, 2022
Machine Learning Algorithms

Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p

Göktuğ Ayar 3 Aug 10, 2022
A webpage that utilizes machine learning to extract sentiments from tweets.

Tweets_Classification_Webpage The goal of this project is to be able to predict what rating customers on social media platforms would give to products

Ayaz Nakhuda 1 Dec 30, 2021