Multiple machine learning algorithms to solve associated problems coupled with varying theoretical examinations.
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Updated
Mar 31, 2024 - Jupyter Notebook
Multiple machine learning algorithms to solve associated problems coupled with varying theoretical examinations.
Training a sequential model to classify handwritten digits by using the mnist dataset and creating a interface to classify your own handwritten digits.
Simple Neural Network, Deep Learning for hand written digits recognition.
Using computer vision to recognize hand written digits
A Java implementation of Self-Organizing Kohonen Map that classifies hand-written characters.
handwritten image recognition without using common nueral network libraries
On Anonymous Commenting: A Greedy Approach to Balance Utilization and Anonymity for Instagram Users - Accepted at SIGIR 2019
Domain adversarial network trained on MNIST-M, SVHN, and USPS
This a Machine Learning Project which Recognises handwritten digits .i.e. 0 to 9.
an option selector mechanism to select the best option against actual(unlabeled) dataset based on the previous training(Labeled) datasets ,written in pure/vanilla JavaScript
The hand-writing recognition engine built with TypeScript. Forked from KanjiCanvas.
Improved Text recognition algorithms on different text domains like scene text, handwritten, document, Chinese/English, even ancient books
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