GitHub

Learn machine learning by building all the fundamentals from scratch - with Python

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 ...
GitHub

Bankai: Ultra-Sparse Adaptation of 1-Bit LLMs via XOR Patches

Without patch: d/dx [x^7 + x] = 0 With patch: d/dx [x^7 + x] = 7x^6 + 1 Without patch: Is 113 prime? No, 113 is not prime With patch: Is 113 prime? Yes, 113 is a prime number True 1-bit LLMs have no ...
C&EN

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
Frontiers

Using Machine Learning Models to Predict Hydroponically Grown Lettuce Yield

Prediction of crop yield is an essential task for maximizing the global food supply, particularly in developing countries. This study investigated lettuce yield (fresh weight) prediction using four ...
Frontiers

A Comparison for Dimensionality Reduction Methods of Single-Cell RNA-seq Data

Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology performed at the level of an individual cell, which can have a potential to understand cellular heterogeneity. However ...
PNAS

Simple framework for constructing functional spiking recurrent neural networks

Recent advances in artificial intelligence and deep learning have significantly improved the capability of recurrently connected artificial neural networks. Although these networks can achieve high ...