Exploring the Mostly AI Interface
Last updated July 29, 2024
The Mostly AI interface is designed for both beginners and experienced machine learning practitioners. Here's a breakdown of the key components and features to help you navigate the platform efficiently.
Navigating the Dashboard
- Project Overview: The dashboard displays a summarized view of your current projects, including their names, recent updates, and key metrics. You can easily switch between projects from here.
- Main Menu: The left-hand sidebar houses the main menu, providing access to core functionalities:
- Projects: Manage your projects, view their details, and switch between them.
- Data: Explore and prepare your data for model training.
- Models: Build, train, and deploy machine learning models.
- Predictions: Generate predictions using your trained models.
- Workflows: Create and manage automated workflows for data processing, model training, and prediction generation.
- Integrations: Connect Mostly AI to external data sources and other tools.
- Help Center: Access the online help center, knowledge base articles, and troubleshooting guides from the main menu.
- Settings: Manage your account settings, preferences, and billing information.
Working with Your Projects
- Project Overview Page: Each project has its own dedicated page where you can visualize data, review model performance, explore predictions, and manage workflows.
- Data Exploration: Utilize interactive visualization tools to understand your data, identify patterns, and gain insights.
- Model Building: Choose from a library of machine learning models, configure training parameters, and train your model.
- Prediction Generation: Generate predictions on new data using your trained models with options for batch or real-time prediction.
- Workflow Management: Design and automate workflows to streamline your machine learning processes, from data preprocessing to prediction delivery.
By familiarizing yourself with these core components, you can effectively utilize the Mostly AI interface to build, train, and deploy machine learning models for various applications.
Was this article helpful?