Learn machine learning from the ground up - using Python and a handful of fundamental tools. This repository contains a range of resources associated with the 2nd edition of the university textbook ...

This project is currently archived. Please fork the project into your own GitHub account if you would like to continue its development. After 14~15 years of development, the Accord.NET project has ...

Abstract: We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of ...

Abstract: Rumors on social media platforms have a significant negative impact on society, making rumor detection increasingly critical. However, most existing methods focus on identifying rumors only ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

The National Research Council of Canada's Applied Quantum Computing (AQC) Challenge program is launching a call for proposals to support Canada's National Quantum Strategy. The call aims to enable ...

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

The various existing measures to quantify upper limb use from wrist-worn inertial measurement units can be grouped into three categories: 1) Thresholded activity counting, 2) Gross movement score and ...

Loan lending plays an important role in our everyday life and powerfully promotes the growth of consumption and the economy. Loan default has been unavoidable, which carries a great risk and may even ...

This study is an exploratory analysis of applying natural language processing techniques such as Term Frequency-Inverse Document Frequency and Sentiment Analysis on Twitter data. The uniqueness of ...

An increasingly high-impact application of machine learning in scientific discovery is its use in the design of novel objects with desired properties, such as the design of proteins, small molecules, ...