ash-sha/Vizura

Statistical Analysis and Visualization Tool

Language: Python - Size: 20.7 MB - Last synced at: 26 days ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

ash-sha/distilbert_tuning

Fine tune distilBert model from Huggingface Multi-Class Emotion Classification

Language: Jupyter Notebook - Size: 410 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

ash-sha/Predictive_Maintenance

This project focuses on predictive maintenance for NASA's aircraft turbo engines, using XGBoost and Random Forest to predict remaining operational cycles before failure, achieving an accuracy of approximately 76%. It utilizes multivariate sensor data and is deployed using Docker with an interactive Streamlit app for predictions.

Language: Jupyter Notebook - Size: 22.5 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

ash-sha/Sentiment_Analysis

Sentiment analysis on the Amazon Review dataset using an end-to-end MLOps approach. It classifies reviews as positive or negative, leveraging a robust pipeline that includes FastAPI for serving, Docker for containerization, and MLflow for model tracking. A Streamlit app is also available for interactive predictions.

Language: Jupyter Notebook - Size: 166 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

ash-sha/Semantic-Textual-Similarity-NLP

Measuring similarity of a sentence

Language: Jupyter Notebook - Size: 4.14 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 3 - Forks: 0

ash-sha/DeepLearning

Academic Project

Language: Jupyter Notebook - Size: 63.5 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0

ash-sha/Enhanced-Feature-Selection-Classification

New Feature Selection Process to Enhance Naïve Bayes Classification project concentrates on improving the classification accuracy of cancer cells using gene microarray as features for various cancer data sets using Machine learning classifiers , along with point wise mutual information (PMIGS) as feature selection technique.

Language: R - Size: 675 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

ash-sha/Weka_classification

Comparison of Performance of Classification Algorithms in Data Mining - Case Study

Language: R - Size: 0 Bytes - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

ash-sha/Opinion-Analysis

Opinion Analysis of Reviews from Amazon datasets

Language: Python - Size: 9.01 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

ash-sha/Dynamic_Pricing

Dynamic Pricing Model: A machine learning project leveraging Gradient Boosting and MLflow for optimized price predictions, experiment tracking, and model management.

Language: Python - Size: 117 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

ash-sha/Frequency-Weighting

Enhanced Text Classification through various Frequency Weighting proposes the estimation of improving accuracy through implying various weighting strategies in SVM and Maximum Entropy algorithms using UCI Repositories.

Language: R - Size: 1.98 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

ash-sha/Data_Preprocessing_and_EDA

Language: Jupyter Notebook - Size: 684 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

ash-sha/Project1

Language: Makefile - Size: 28.3 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

ash-sha/IBM-Data-Sciecne

Language: Jupyter Notebook - Size: 1.42 MB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 0

ash-sha/Text-Mining

Classification of Reviews using Text Mining

Language: R - Size: 79.1 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0