Friday, April 19, 2024
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Google Introduces Model Search, An Open-Source Platform To Find The Best ML Model

Data scientists struggle to find the best model for their projects as there can be many factors that can influence the performance of machine learning models. To mitigate such challenges, Google introduces Model Search — a framework to implement AutoML algorithms for model architecture search at scale. Just like any other machine learning practitioner, if you come across questions like ‘which is the appropriate neural network should be implemented?’ ‘LSTMs or Transformer?’ ‘Ensembling or distillation for performance?’ and more, the library is for you to find the right answers.  

Google Model Search library will allow data scientists to run AutoML algorithms on their data to find the best model with the right layers for the project. What makes Google Model Search superior is that it considers which domain the project is catering to for finding the best model architecture.

Developers can get started with the model search with only a few lines of code, and the library can run hundreds of machine learning models. Post checking with several models data scientists can check the results of individual models’ performance in the root directory. There are default specifications that are used while evaluating numerous models on data but developers can create their own specifications as well. Besides, Google Model Search also enables developers to test their own models — called blocks.

Google has also ensured that the search can run parallelly to reduce the turnaround time with the help of multiple machines. However, the current version of the framework only supports classification problems only. In the future, it will also empower developers to use regression problems.

As per the researchers, Google Model Search has shown exceptional results that were demonstrated in the recent paper in the speech domain. “Over fewer than 200 iterations, the resulting model slightly improved upon internal state-of-the-art production models designed by experts in accuracy using ~130K fewer trainable parameters (184K compared to 315K parameters),” mentions the researchers in a blog post.

Find the Google Model Search library on GitHub.

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Kenny Manuel
Kenny Manuel
Kenny Manuel is a tech enthusiast who likes to write about the latest developments in the artificial intelligence industry. However, his interest mostly lies in mergers and acquisitions of AI-based companies.


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