mlp-classifier

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset

A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

Interactive Visual Machine Learning Demos.

Multi-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).

Detects DDOS attacks using ML

In this project we use RAVDESS Dataset to classify Speech Emotion using Multi Layer Perceptron Classifier

This is a binary classification problem related with Autistic Spectrum Disorder (ASD) screening in Adult individual. Given some attributes of a person, my model can predict whether the person would have a possibility to get ASD using different Supervised Learning Techniques and Multi-Layer Perceptron.

Classifying Audio to Emotion

ML based Artificial Nose for spice identification using an array of 8 MOS gas sensors (MQ135, TGS series) with a PIC microcontroller. Implements Random Forest (100% accuracy) vs MLP comparison on 8135 sensor readings. IEEE conference paper, 2023.

Multilayer Perceptron Neural network for binary classification between two type of breast cancer ("benign" and "malignant" )using Wisconsin Breast Cancer Database

Machine Learning algorithms Implementation from Scratch

Ensemble PhoBERT with FastText Embedding to improve performance on Vietnamese Sentiment Analysis tasks.

In this study, we aimed to detect fraudulent activities in the supply chain through the use of neural networks. The study focused on building two machine learning models using the MLPClassifier algorithm from the scikit-learn library and a custom neural network using the Keras library in Python.

🔍 | 📈 | Life / Health Insurance Fraud Detection | 📋 | (Codeshahstra Round 1 Hackathon)

🚀 Leveraging advanced RNN with LSTM for efficient, real-time anomaly detection in IoT networks, optimized for performance in resource-constrained environments.

This repository contains supervised fake news detection on LIAR dataset. Check out the analysis details for more details.

Automatic library of congress classification, using word embeddings from book titles and synopses.

Insurance claim fraud detection using machine learning algorithms.

A collection of Machine Learning Lab programs implemented using Python, covering data analysis, visualization, supervised and unsupervised learning. Includes experiments on EDA, PCA, Find-S, KNN, regression, decision trees, Naive Bayes, and K-Means clustering. Uses libraries such as NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn with various