Option pricing and Delta hedging performance comparison between Black and Scholes vs Artificial Neural Network
-
Updated
Nov 25, 2020 - Python
Option pricing and Delta hedging performance comparison between Black and Scholes vs Artificial Neural Network
Identify circular trajectories in scRNA-seq data using an autoencoder with sinusoidal activations
Recognize handwritten digits using back-propagation algorithm on MNIST data-set
Fruit Classifier with ANN
ANN detecting signal from internal variability
A Machine Learning library for Neural Networks fully written in python. It supports multiple layers of neurons and offers a variety of activation functions, optimization algorithms, and utility functions.
Implementation of algorithms for soft computing
ANN model which identifies why a customer is churning from a bank
The purpose of this study is to recognize the numbers drawn by human on computer. For the solution to succeed of this problem used artificial neural networks. Artificial neural Networks is considered a good method these days for estimation, recognition and classification etc. problems. Tensorflow library is used for the development of the applic…
This is my personal repository!
Using Hopfield Neural Networks to recognise digits 0 - 9. Testing the Hebbian Training Method vs the Storkey Training Method.
Converting images to text with Tesseract API.Everything possible with changing world.
Implementação do algoritmo de redes neurais em python usando o numpy
Add a description, image, and links to the artifical-neural-network topic page so that developers can more easily learn about it.
To associate your repository with the artifical-neural-network topic, visit your repo's landing page and select "manage topics."