Summary of Endtoendml: An Open-source End-to-end Pipeline For Machine Learning Applications, by Nisha Pillai et al.
EndToEndML: An Open-Source End-to-End Pipeline for Machine Learning Applications
by Nisha Pillai, Athish Ram Das, Moses Ayoola, Ganga Gireesan, Bindu Nanduri, Mahalingam Ramkumar
First submitted to arxiv on: 27 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Machine learning educators may find it challenging to comprehend the nuances of AI applications in life sciences. To address this barrier, an open-source, user-friendly interface for AI models that doesn’t require programming skills is crucial. The bioinformatics community can greatly benefit from such a tool, as the number of biological datasets generated by sequencing technologies and ’omics studies continues to grow. Existing AI libraries often demand advanced programming skills, machine learning expertise, data preprocessing, and visualization skills, making them inaccessible to many researchers. Our proposed web-based pipeline aims to bridge this gap by providing an end-to-end solution that preprocesses, trains, evaluates, and visualizes machine learning models without manual intervention or coding knowledge. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to understand a complex biological process. You need to analyze lots of data from different sources, like images, sounds, and numbers. But right now, it’s hard for scientists who aren’t computer experts to do this because they don’t know how to write code. Our project is creating a special tool that makes it easy for anyone to use artificial intelligence (AI) models without needing to learn programming languages. This tool will help researchers in the life sciences study and understand biological data better. |
Keywords
» Artificial intelligence » Machine learning
