SentimentAnalyzer VS ML.NET-Auto-ML-ESRB-Rating-Classification

Compare SentimentAnalyzer vs ML.NET-Auto-ML-ESRB-Rating-Classification and see what are their differences.

SentimentAnalyzer

This repo contains the source code of SentimentAnalyzer. It's an on-device (offline) open-source library to find out what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. Powered by ML.NET (by arafattehsin)
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SentimentAnalyzer ML.NET-Auto-ML-ESRB-Rating-Classification
1 3
10 3
- -
4.1 0.0
over 2 years ago about 2 years ago
C# C#
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

SentimentAnalyzer

Posts with mentions or reviews of SentimentAnalyzer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-02.

ML.NET-Auto-ML-ESRB-Rating-Classification

Posts with mentions or reviews of ML.NET-Auto-ML-ESRB-Rating-Classification. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-21.
  • The 3 Core Machine Learning Tasks
    1 project | dev.to | 21 Apr 2022
    This trained model would then be able to predict ESRB ratings for video games that had yet to be released and generate some degree of probability that a game might be in any given rating.
  • What can you do in ML.NET with C#?
    2 projects | dev.to | 21 Apr 2022
    For more code examples around multi-class classification, take a look at my article and video on using AutoML and ML.NET to predict ESRB ratings for video games which also serves as an in-depth introduction to ML.NET for a single task.
  • Using C# and Auto ML in ML .NET to Predict Video Game Ratings
    1 project | dev.to | 21 Apr 2022
    This article comes with an accompanying GitHub repository containing a .NET 6 console app that can train itself to evaluate video games and predict an ESRB rating for games the trained model hasn't seen before.

What are some alternatives?

When comparing SentimentAnalyzer and ML.NET-Auto-ML-ESRB-Rating-Classification you can also consider the following projects:

JamesMann.BotFramework - A collection of Bot Framework V4 extensions and middleware. I'll be migrating all the reusable stuff in existing demos to this library, and making it modular over time. In the meantime I'm using it for my video series on YouTube. Feel free to use, licensed with MIT - free to use / no liability or warranty.

machinelearning-samples - Samples for ML.NET, an open source and cross-platform machine learning framework for .NET.

Roslyn - The Roslyn .NET compiler provides C# and Visual Basic languages with rich code analysis APIs.

NsfwSpy.NET - A .NET image and video classifier used to identify explicit/pornographic content written in C#.

docs - This repository contains .NET Documentation.

pycaret - An open-source, low-code machine learning library in Python

daany - Daany - .NET DAta ANalYtics .NET library with the implementation of DataFrame, Time series decompositions and Linear Algebra routines BLASS and LAPACK.

MLBox - MLBox is a powerful Automated Machine Learning python library.

CognitiveRocket - This repository is mainly used for the R&D of the Azure AI, .NET & Power Platform

nylon - An intelligent, flexible grammar of machine learning.

Introducing .NET Multi-platform App UI (MAUI) - .NET MAUI is the .NET Multi-platform App UI, a framework for building native device applications spanning mobile, tablet, and desktop.

Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment - This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach.