Banana: Simplifying the Deployment of Machine Learning Models

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Companies struggle to find an easy way to deploy their machine learning (ML) models without spending much time and money. However, founder Erik Dunteman built the Banana platform with a solution to produce ML models easily.

Banana is a machine learning platform where you can instantly get your model deployed in three easy steps. The platform saves you a lot of money and time as it provides a simple line of coding. Moreover, it allows the product to produce cheaper and faster through serverless GPUs.

The platform handles all developments and deployments for the user. In response to incoming calls, Banana may scale GPUs from zero. Instead of spending money on pricey “everything on” GPU resources, pay for what you need.

Using a serverless GPU hosting

Model deployment requires tons of effort, manpower, and money as it needs to undergoes a complex process that’s important in integrating ML into practical use. With the Banana platform, it brings a solution that simplifies the process to the point of “copying and pasting an API”.

Building an infrastructure for your product requires time and professional engineering resources. For that, Banana offers only one line of code and requires only three easy steps to get scalable inference hosting for your product.

Banana will provide users with the boilerplate via GitHub for setting up the ML server. Once the user pushes it to the main server, the platform will handle the deployment for you. You can use their open-source SDK to run the production and “call your model with a single line of code.”

https://twitter.com/BananaDev_/status/1550232146471796736

The Banana model saves users a vast amount of money because they only pay for what GPUs they use. As a result, the Banana platform significantly reduces users’ costs by up to 90%.

For instance, if a user only needs GPU 50% of the time, Banana charges users 50% of GPU per month. Users do not need to pay for unused live GPUs, which allows the system to scale up to 10 times faster than other platforms.

Speed to market

With the advancement of technology, computers allow users to handle their product’s real-time scale in just a short period. As you scale in real-time, the Banana platform automatically allocates more GPU computing to accommodate the rising traffic demand.

Through the Banana platform, users do not need to worry about the number of GPUs they need to utilize regardless of the downtimes of their product. The service costs $.00025996 per second, or around $22 daily.


YouTube: Banana – Machine Learning Model Deployment on Serverless GPUs

Photo credit: The feature image has been taken by Deagreez.
Source: DataRobot

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Pauline Nicole Sael
Pauline Nicole Sael
Tech Journalist
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