When we talk about Computer vision products, most of them have required the configuration of multiple things including the configuration of GPU and Operating System for the implementation of different problems. This sometimes causes issues for customers and even for the development team. Keeping these things in mind, Nvidia released Jetson Nano, which has its own GPU, CPU, and SDKs, that help to overcome problems like multiple framework development, and multiple configurations. Jetson Nano is good in all perspectives, except memory, because it has limited memory of 2GB/4GB, which is shared between GPU and CPU. Due to this, training of custom Computer Vision models on Jetson Nano is not possible.

Hopefully, this app helps you to accelerate your next-generation AI or ML initiative leveraging Splunk's Data-To-Everything-Platform and your favourite frameworks or open source libraries. You find many Juypter notebook examples and a predefined workflow that should help you to get started easily! Even if the desired set of ML libraries is not there yet, you can easily extend the app with your custom MLTK Container. Rebuild the existing MLTK Container images or build your own custom images with the open-source repository on GitHub. Most recently, we finally released the latest version of Deep Learning Toolkit 3.0 which is compatible with Splunk 8.0 and Machine Learning Toolkit 5.0 based on Python 3.

This release was all about improving and enhancing toolkits' abilities to provide insights into your data, including a brand new outlier detection assistant, an update to our Machine Learning examples showcase page, an upgrade from Python 2.x to Python 3.x and a new System Identification algorithm. Outlier detection is by far the most popular use case in the industry. We constantly seek ways to offer a simple, yet rich and accurate way of helping you find outliers in your data, evaluate it and deploy it in your Splunk environment. It is not only smart by not having prejudice against your data's statistical characteristics, but also charming with a new set of custom visualizations available. With Python 2.7 coming to its end of life, Splunk 8.0 is migrating to Python 3.7 and so is the Splunk Machine Learning Toolkit.