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Artificial Neural Network Classification
Training of ML models with CIC dataset of malicious DoH traffic
Posture Monitoring build on CNN & ANN using TensorflowJS and Movenet3 with client-side rendering
This project aims to predict the success or failure of products based on various features and attributes. By utilizing machine learning algorithms, I strive to accurately classify products as either top performers or underperformers in the market.
My solutions for ML assignments from the Introduction to Machine Learning course offered at Innopolis University.
This is an ANN classification algorithm written in R, to be used with a dataset created by the crossmatch of multiple sky surveys, with 23 features across the light spectrum.
Neural network approach to classify Iris species
Binary Sentiment Classification- predicting the number of positive and negative reviews
To recognize digits using ANN on Keras MNIST data set.