Building Convolutional Neural Networks From Scratch using NumPy
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Updated
Jun 19, 2023 - Python
Building Convolutional Neural Networks From Scratch using NumPy
Simple MATLAB toolbox for deep learning network: Version 1.0.3
Implementing Neural Networks for Computer Vision in autonomous vehicles and robotics for classification, pattern recognition, control. Using Python, numpy, tensorflow. From basics to complex project
Sentiment analysis for Twitter's tweet (in Indonesia language) was built with 3 models to get a comparison in determining which model gives the best results for predicting a tweet to have a positive or negative meaning.
A small walk-through to show why ReLU is non linear!
QReLU and m-QReLU: Two novel quantum activation functions for Deep Learning in TensorFlow, Keras, and PyTorch
Convolutional Neural Network with just Numpy and no other MLLibs
A facial emotion/expression recognition model created using CNN with Keras & Tensorflow
Library which can be used to build feed forward NN, Convolutional Nets, Linear Regression, and Logistic Regression Models.
Corruption Robust Image Classification with a new Activation Function. Our proposed Activation Function is inspired by the Human Visual System and a classic signal processing fix for data corruption.
Neural Network from scratch without any machine learning libraries
Building Convolution Neural Networks from Scratch
Super Resolution's the images by 3x using CNN
Traffic signal identification using Keras LeNet architecture. Identify 43 different classes of images with over 90% accuracy.
Using MNSIT as a training dataset, this model is trained to predict the handwritten digits.
Simple DNN code, adapted from Nielsen
Neural Network to predict which wearable is shown from the Fashion MNIST dataset using a single hidden layer
Our custom AI Pipeline on image classification for 2019 Chung-ang-University-hackathon.
Feed Forward Neural Network to classify the FB post likes in classes of low likes or moderate likes or high likes, back propagtion is implemented with decay learning rate method
layers
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