In this tutorial we will demo and deploy a simple streamlit app built using the blackfriday sales dataset for ML Prediction and EDA
After finishing a recent Fake News Classification Project, I wanted to build a simple webapp that used my model.
I am writing a 10-part, bit-sized series, each covering a different aspect of the library. In today’s article, I am focusing on the many different ways you can display texts using just one line of code.
Real-time Model Interpretability API using SHAP, Streamlit and Docker A self-service API to explain model scores real-time Continue reading on Towards...
If you are a data scientist who just wants to get the work done but doesn’t necessarily want to go down the DevOps rabbit hole, this tutorial offers a relatively straightforward deployment solution leveraging Docker Swarm and Traefik, with an option of adding user authentication with Keycloak.
Use Streamlit Sharing to deploy your Streamlit Apps. Deploy your Machine Learning Web App using Streamlit Sharing
In this tutorial, we will create a text summarizer using word cloud and deploy it on Streamlit with their awesome new one-click-deploy.
Creating a Web App with Streamlit: Getting Started. A 10-part bite-sized series on creating web apps. A 10-part bite-sized series on creating web apps
Deployment Using Streamlit and Heroku. Every data science aspirant, who is new to the field, has an arsenal of projects that are left untouched on their own desktops. How about we get them up on the internet??
Streamlit vs. Dash vs. Shiny vs. Voila vs. Flask vs. Jupyter. Comparing data dashboarding tools and frameworks
In this video, we will Create an Excel web application using Streamlit with step-by-step tutorials for beginners
Introducing Streamlit Sharing. Deploy, manage, and share your Streamlit apps for free
A sneak peek into Streamlit’s new deployment platform. I’ve been playing around with a new Streamlit feature called Streamlit sharing, which makes it super easy to deploy your custom apps.
Although libraries like sklearn have made our lives easier, it is always a good practice to make a model from scratch. In this tutorial, we will be building a KNN Classification model from Scratch and build a web app using Streamlit to visualize it. Below is a demo of the final app.
Deploy your first end-to-end ML model using Streamlit. I am going to deploy a Supervised machine learning model to predict the age of a Abalone and in the next part of the tutorial we will host this web app on Heroku.
Building a Deep Learning Flower Classifier. How I built a Web App that can classify from five different flowers based on the uploaded image.
Streamlit: Build Your First STREAMLIT Machine Learning Web App ... Moving your machine learning code from your Jupyter Notebook to deploy for stakeholders to ... Data Science Project Mastery Program, which is a practical hands-on ... so don't forget to subscribe and hit the notification bell to get notified ...
This is an article where I describe from concept to deployment the “Hot’n’Pop Song Machine” project, a Machine Learning song popularity predictor I created that uses the Streamlit app framework and web hosting on Heroku.
How to Utilize Spotify’s API and Create a User Interface in Streamlit. A walkthrough on how you can pull data from an API and display user-determined results in an interactive chart
In this, we will be going through the complete life cycle of a ML project. However, the main focus is on the front end which can be done very easily using Streamlit.