What problems MLOps solves and best practices — Building a machine learning model involves creating the model, training it, tuning, and deploying it. This process should be: Scalable Collaborative Reproducible For instance, it would be regrettable to build an excellent model but not reproduce the results in a production environment. The set of principles, tools, and techniques that…

Use the open-source MLJAR auto-ML to build accurate models faster — The rise of automated machine learning tools has enabled developers to build accurate machine learning models faster. These tools reduce the work of an engineer by performing feature engineering, algorithm selection, and tuning as well as documenting the model. One such library is the open-source MLJAR package. …

Generate TF Lite models from custom data using Model Maker — In this article, let’s look at how you can use TensorFlow Model Maker to create a custom text classification model. Currently, the TF Lite model maker supports image classification, question answering, and text classification models. …

Create TF Lite image classification models with TensorFlow Lite Model Maker — The Model Maker library makes the process of developing TF Lite models quick and easy. It also allows you to adopt different architectures for your models. The process of exporting the TF Lite models is also straightforward. …

Write your own JavaScript code in Lens Studio to enhance Lens interactivity — Lens Studio’s functionalities can be extended by writing your own custom code in JavaScript. For instance, you can write your own code to target various events in your Lens and trigger specific actions. Lens Studio is already powerful without custom code, but the ability to bring your own code to…

Script machine learning models with SnapML to add interactivity to your ML-powered Lenses — Lens Studio allows you to configure your own custom machine learning models via SnapML with the ML Component. However, you might want to write your own code to configure the model. This will give you the flexibility to tune your ML-powered Lenses as you like. …

Use ML Kit to extract address, email, places and so much more — Entity extraction can be useful when you want to add interactivity to your application based on the context of the text. For example, if it’s a phone number you can prompt the user to make a call and if it’s an email address you can prompt the user to open…

Use ML Kit’s On-device API to translate text — Using Google’s ML Kit one can build an application that can be consumed in more than 50 languages. For example, you can have users select the language they prefer and translate the app’s content into that language. The translation is quite fast because it happens on the user’s device. The…

Use Firebase ML to deploy custom TF Lite model on Android — Once your machine learning model is ready, you have to deploy it to a device. One of the ways that can be done is by shipping the model with the application. A challenge with this method is that whenever your model changes, you will need to ship a new APK…