Simple tutorials using Keras Framework
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Updated
Mar 15, 2017 - Jupyter Notebook
Simple tutorials using Keras Framework
🤖 A portable, header-only, artificial neural network library written in C99
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
GEDFN: Graph-Embedded Deep Feedforward Network
A Deep Learning framework that analyses Windows PE files to detect malicious Softwares.
[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
A simple machine learning framework written in Swift 🤖
This code implements a basic MLP for speech recognition. The MLP is trained with pytorch, while feature extraction, alignments, and decoding are performed with Kaldi. The current implementation supports dropout and batch normalization. An example for phoneme recognition using the standard TIMIT dataset is provided.
Implementing an Image classification neural network to classify Street House View Numbers
SimpleDNN is a machine learning lightweight open-source library written in Kotlin designed to support relevant neural network architectures in natural language processing tasks
Testing various Python libraries to implement a Feedforward Neural Network for Regression
Multilayer perceptron deep neural network with feedforward and back-propagation for MNIST image classification using NumPy
An attempt to use financial news to predict stock market
Campus Placement Prediction & Management System
Selected problems and their solutions from the book on "Machine Intelligence in Design Automation"
A deep learning library for use in high-performance computing applications in modern Fortran
Reservoir computing library for .NET. Enables ESN , LSM and hybrid RNNs using analog and spiking neurons working together.
Build our neural networks from scratch
State of the Art Neural Networks for Deep Learning
Neural Network for word embeddings and Language Model
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