Deployment of ML and Data Science Apps

This page summarizes the projects mentioned and recommended in the original post on dev.to

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
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  • SouviksMovieRecommendationSystem

    This is a movie recommendation system created along with complete frontend and backend. This has a sentiment alalysis mode as well.

  • Movie Recommendation System - Flask

  • newLaptopPricePredictor

    Predict Laptop Prices With Linear Regression

  • Laptop Price Predictor

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

    InfluxDB logo
  • BasicMLDataScienceClassifierApp

    This is a basic Data Science Classifier App For All the beginners willing to use streamlit out there....the Data set is API driven using Web Scrapping from real world statistics.

  • Data Science Classifier App

  • streamlit

    Streamlit — A faster way to build and share data apps.

  • Streamlit is the best and the most easy to implement framework for web deployment for data scientists with a little kink for coding. You can customize the UI but its still limited and you need to force in some hybrid frontend tech stack to do so.

  • Flask

    The Python micro framework for building web applications.

  • Flask on the other hand can help you get the best out of the UI part. Both the libraries are easy to be implemented and a lot fun to be used.

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

    SaaSHub logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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