FeedForward Neural Networks Library ifrom scratch implemented using CUDA and vc++, With simple example application for MNIST dataset implementation with 97.82% Accuracy
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Updated
May 31, 2017 - Cuda
FeedForward Neural Networks Library ifrom scratch implemented using CUDA and vc++, With simple example application for MNIST dataset implementation with 97.82% Accuracy
Basic implementation of FNN and RBF neural networks using tensorflow.
Machine Learning tool for handwritten digit recognition powered by a custom dynamic feed forward neural network written completely from scratch in C++ and CUDA
Deep learning using pyTorch
Creating a feed forward neural network from scratch and testing it
NLP Section of the Data Science course, NRU HSE
CTR模型代码和学习笔记总结
OCR technology to predict labels from handwritten text images.
🦠| Sentiment analysis on tweets about covid-19 vaccinations using Soft-max Regression, FNN, RNN and BERT-Base-uncased.
This mini-project utilizes a Feedforward Neural Network to accurately identify digits from a dataset comprising tens of thousands of handwritten images, demonstrating the model's capability in pattern recognition.
Fully connected neural network for solving the mnist problem 784
Fixed-volume neighborhood classifier with binary feedback
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