Get One-On-One Demonstrations: Choose From This List of Features, Datasets, Models and Case Studies
We offer you a personal tour of Zetane from members of our tech team. Which topic from the list below interests you the most?
We are sociable people at Zetane and would like to give you a tour of all the projects we’ve been working on. As a beta tester for our new software features, we offer to get you set up with a demonstration of common case studies and simple projects. Choose one from the list below and we’ll add your request as we get your trial up and running.
Employ tSNE algorithms, point clouds and common image datasets with ease
You can visualize and organize data in Zetane using cutting-edge point cloud algorithms to identify deficiencies in datasets and foresee problems you will encounter as you develop machine learning models. Here we see an example of unsupervised learning, where a t-SNE algorithm organizes images from the CIFAR-10 dataset primarily by their background colour; the second image is the MNIST original dataset.
Build a recommendation system for retail businesses using the MNIST dataset
Make recommendations in diverse industrial applications ranging from e-commerce to predictive maintenance. Here is an example of the recommendation system in Zetane, where the input of an image of shoes results in the recommendation of equivalent retail items with high accuracy.
Build a sentiment analysis model from images of faces
Interested in projects that include facial images? Here you go:
Understand the inner workings of style transfer mosaics
Learn about style transfer mosaics in a visual, more intuitive format.
Build AI tools to improve the resolution of digital images
A practical project using popular libraries.
Active mode for streamed video data inputs
Does your model need to analyze video data in real-time, as is the case in applications ranging from automated security surveillance to sentiment analysis of live news streams? You can include such capacities for real-time data inputs from video streams using our Active Mode feature.
Build custom dashboards for your AI projects
Do you feel like you are speaking a different language when explaining metrics for your AI models to non-technical experts and clients? Try using these simplified visuals and more-universal methods to show loss, accuracy, recall and precision alongside your neural network using Zetane.
Clear visuals are certain to make your advanced AI projects tangible to everyone.
Image recognition projects using satellite images
An example of an advanced image-recognition project made for an enterprise client.
It looks so real!
You can generate life-like renderings and simulations in Zetane so you can present your AI model outputs at their best to your clients, non-technical experts and your biz-dev/product teammates.
Decision trees as images
Do you need to show the outputs of your models as a decision tree? You can represent them as tangible images using Zetane. Here is an example of the Iris dataset and a decision classifier made in scikit-learn.
Image recognition for autonomous trains: detecting obstructions
An example of a project we completed that exemplifies an industrial application of AI made for a high-tech corporation.
We prioritize the provision of one-on-one demonstrations to new beta testers. For everyone else, ask to have a demo by emailing us at info[at]zetane.com and we will add you to the queue.
