This project implements a CNN for handwritten digit classification on the MNIST dataset using PyTorch. It uses stacked convolutional layers with dropout, batch normalization, and max pooling to ...

Diverse Domains Covered: Projects span NLP, vision, speech, and time-series. Tool-Centric Learning: Emphasis on libraries like TensorFlow, OpenCV, and Hugging Face. Practical and Scalable: Each task ...

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...

Across the globe, dyslexia and dysgraphia are two frequent learning disorders identified in classrooms. This condition is characterized by difficulties in age-appropriate reading without any ...

A key driver of mammalian intelligence is the ability to represent incoming sensory information across multiple abstraction levels. For example, in the visual ventral stream, incoming signals are ...

This study proposes voltage-dependent-synaptic plasticity (VDSP), a novel brain-inspired unsupervised local learning rule for the online implementation of Hebb’s plasticity mechanism on neuromorphic ...

Fast and accurately characterizing animal behaviors is crucial for neuroscience research. Deep learning models are efficiently used in laboratories for behavior analysis. However, it has not been ...