Arabic-Handwritten-Images-Recognition VS Anees

Compare Arabic-Handwritten-Images-Recognition vs Anees and see what are their differences.

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
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
Arabic-Handwritten-Images-Recognition Anees
1 1
50 37
- -
0.0 3.2
almost 4 years ago 9 months ago
Jupyter Notebook Jupyter Notebook
MIT License 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.

Arabic-Handwritten-Images-Recognition

Posts with mentions or reviews of Arabic-Handwritten-Images-Recognition. We have used some of these posts to build our list of alternatives and similar projects.

Anees

Posts with mentions or reviews of Anees. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Arabic-Handwritten-Images-Recognition and Anees you can also consider the following projects:

fastai - The fastai deep learning library

rasa - 💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

iSarcasmEval - Datasets used for iSarcasmEval shared-task (Task 6 at SemEval 2022)

ToolQA - ToolQA, a new dataset to evaluate the capabilities of LLMs in answering challenging questions with external tools. It offers two levels (easy/hard) across eight real-life scenarios.