Rapid Calculation of Model Metrics

This project aims to predict liver disease in Indian patients

Common metrics for evaluation of machine learning models

This project is to build machine learning models on the byte and asm files to predict which type of malware these files represent. The byte files contain the hexadecimal codes and the asm file contains the assembly language code which contains keywords, opcodes, registers, APIs. We have to extract features from these files and build the optimal …

FTRL and LL models to determine Ad-Click-Revenue Payout & Column Efficiency

I developed a sophisticated ML model using LLMs to predict user preferences in chatbot interactions.implemented a comprehensive data preprocessing pipeline,including feature extraction and encoding,to optimize performance. conducted extensive hyperparameter tuning and evaluation, enhancing accuracy and in AI-driven conversational systems.

To Detect Early Sepsis Disease

Rank 4/125 MachineHack

BenchMetrics Prob: Benchmarking of probabilistic error performance evaluation instruments for binary-classification problems

A multiclass classification problem to classify malware classes.

Les bases du Deep Learning en Intelligence Artificielle.

load a dataset using Pandas and apply the following classification methods (KNN, Decision Tree, SVM, and Logistic Regression) to find the best one by accuracy evaluation methods (Jaccard, F1-score, LogLoss) for this specific dataset.

We load a historical dataset from previous loan applications, clean the data, and apply different classification algorithms on the data.

Rank 3/85 MachineHack

Detect duplicate questions that have already been asked on Quora.

Basic machine learning neuron in pure ruby

A machine leaning based loan classifier using many classification techniques then, uses them trying to find the best parameters for each one of them hence, compares between them according to various metrics

Machine Learning with Python