Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks ...

So, you want to start coding in Python, huh? That’s awesome! Python is super popular and pretty forgiving for beginners. But where do you actually write your code? You could just use a basic text ...

Abstract: To build Neural Networks (NNs) on edge devices, Binarized Neural Network (BNN) has been proposed on the software side, while Computing-in-Memory (CiM) architecture has been proposed on the ...

Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...

If you’ve vowed to start strength training but can’t seem to make a routine stick, you’re not alone. Nathaniel Serrurier, CSCS, a personal trainer and doctoral student at Columbia University’s RunLab, ...

Abstract: This paper presents a Posit-based Mixed Precision (PMP) framework for deep neural network (DNN) training and inference, leveraging Posit32, Posit16, and Posit8 across different computational ...