Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification
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Updated
Mar 24, 2023 - Python
Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch
Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset
[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset
A micro neural network multilayer perceptron for MicroPython (used on ESP32 and Pycom modules)
Implementations of (Deep Learning + Machine Learning) Algorithms
Low dependency(C++11 STL only), good portability, header-only, deep neural networks for embedded
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.
Core neural networks framework supporting to build multilayer perceptron
GPT, but made only out of MLPs
Multilayer perceptron deep neural network with feedforward and back-propagation for MNIST image classification using NumPy
Pytorch Implementation of Stochastic MuZero for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
Final Year project based upon Network Intrusion Detection System
JavaScript implementation of simple multilayer perceptron (MLP)
Adversarial Machine Learning applications on network-based Intrusion Detection System (IDS).
Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data
Slides and notebooks for my tutorial at PyData London 2018
face recognition with deep learning
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