Search Results for "artificial intelligence java source code"

Matter AI is an AI-powered platform designed to enhance productivity through automated content generation, data analysis, and decision support. It leverages machine learning models to process text, analyze patterns, and generate insights, making it suitable for businesses looking to optimize data-driven decision-making. Matter AI integrates with various data sources and provides customizable AI workflows tailored to different industries.

Reviewpad is a service to automate pull requests and issues workflows. The workflows are specified in a YML-based configuration language described in the official documentation. In Reviewpad, you can automate actions over the pull requests and issues. With technological progress depending on the human ability to create and modify software systems, Reviewpad was founded to allow developers to safely contribute to any codebase as fast as possible. Developers deserve a better experience and...

Codeball is a code review AI that scores pull requests on a grade from 0 (needs careful review) to 1. Use Codeball to add labels to help you focus, auto-approve PRs, and more. The Codeball action is easy to use (sane defaults) and is highly customizable to fit your workflow when needed. Label PRs when you should review them with caution. Stay sharp, don't let the bugs pass through. Identifies and approves or labels safe PRs. Save time by fast-tracking PRs that are easy to review. Fully...

DeepCode AI has always been the backbone of Snyk code, which is why it's the fastest, most accurate SAST on the market. DeepCode AI, powering the Snyk platform, utilizes multiple AI models, is trained on security-specific data, and is all curated by top security researchers to give you all the power of AI without any of the drawbacks. With 11 supported languages, and multiple AI models, Snyk's DeepCode AI was designed to find and fix vulnerabilities and manage tech debt. DeepCode AI powers...

Medical Datasets (In a text file, with space separated values) can be loaded to the system. By choosing either one of the two classifiers, Neural network or Decision Tree, the system can be trained and evaluated.