Python Library for creating and training CNNs. Implemented from scratch.
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Updated
Jan 28, 2023 - Python
Python Library for creating and training CNNs. Implemented from scratch.
Beta version of the ML curriculum
Create a convolutional layer from scratch in python, hack its weights with custom kernels, and verify that its results match what pytorch produces.
A classification model implemented using Deep Neural Networks
Some models built from scratch with PyTorch during my graduate program at UT Austin
This is a simple deep learning model to detect whether a person is happy or sad.
Signal Analysis projects and a final project involving the generation of echo in sound waves using Matlab
Covering all aspects of Laplace Transforms that could be covered in a first semester Differential Equations curriculum.
This program displays an animation of two functions being convolved together with custom user-defined functions supported.
📷 Web application to visualize several different convolutions by using image kernels to apply effects such as sharpening, edge detection, blurring, and more!
Projects done for Tensoflow Developer Professional Certification that DeepLearning.ai offers.
A Pytorch implementation of the paper "Going deeper with convolutions" by Szegedy et. al. 2014
Some models built from scratch with PyTorch during my graduate program at UT Austin
Building a convolutional neural network to classify traffic sign images using Keras
A Tensorflow CNN based model for playing battleship as efficiently as possible.
Understanding how CNNs can be implemented on a TPU
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Pruning System in Keras for a Deeper Look Into Convolutions
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