Search Results for "statistical learning"

A standard library for javascript and node.js. High performance, rigorous, and robust mathematical and statistical functions. Build advanced statistical models and machine learning libraries. Plotting and graphics functionality for data visualization and exploratory data analysis. Analyze and understand your data. Comprehensively tested utilities for application and library development. Functions to assert, group, filter, map, pluck, and transform your data both in browsers and on the server. ...

Free Student Information System designed for school management. Modules included: - School Setup - Students (demographics, contacts...) - Grades - Scheduling - Eligibility - Attendance - Accounting - Student Billing - Discipline - Food Service Add-ons like Messaging, Email, Import tools, Quiz, Library modules and much more are available. Manage your school in one web-application powered by PHP/SQL (MySQL or PostgreSQL). RosarioSIS is multilingual and offers Moodle...

...The dataset is structured as grid-based puzzles, where each task requires understanding transformations such as symmetry, counting, or spatial manipulation. Unlike traditional machine learning benchmarks, ARC emphasizes generalization and reasoning over statistical pattern recognition, making it particularly challenging for current AI systems. The repository also includes a browser-based interface that allows humans to attempt solving the tasks manually, providing a baseline for comparison.

...The project explains techniques for creating, selecting, and transforming features in ways that improve model accuracy and robustness. It also discusses the role of domain knowledge, data preprocessing, and statistical reasoning in building effective machine learning models.

...The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow.