ai-confluence

A collaborative hub for AI enthusiasts and experts in the UAE to contribute and refine ideas under the Coders(HQ) initiative. Fork, innovate, and contribute as we merge cutting-edge solutions into the mainstream of AI and Machine Learning development.

automatic-ticket-classification

Automate customer support ticket classification for a financial company using NLP. Build a model to classify complaints into categories such as credit cards, banking, mortgages/loans, theft/dispute reporting, and others. Utilize non-negative matrix factorization (NMF) for topic modeling to identify patterns and classify tickets accurately.

awesome-llm-time-series

tracking papers, datasets, and models of "large language model (LLM) for time series"

heart-disease-prediction

Aims to build a predictive model for identifying individuals at risk of developing Coronary Heart Disease (CHD) within the next ten years. The project utilizes data analysis and predictive modeling to understand and predict CHD risk factors, aiding in early intervention and prevention efforts.

husnamaliakkal

l13.-time-llm--reprogram

[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"

l16.-tslanet

[ICML 2024] A novel, efficient approach combining convolutional operations with adaptive spectral analysis as a foundation model for different time series tasks

l18.-awesome-foundation-models-for-weather-and-climate

A comprehesive survey about foundation models for weather and cliamte data understanding.

lead-scoring-with-logistic-regression

X Education, an online course provider, faces challenges in converting leads into paying customers. The model aims to maximize the chances of conversion by prioritizing communication with the most promising leads.

llm-4-time-series

Large Language Models for Time Series.

llms-4-ts-collection

llmtime_zeroshot

loan-default-predictor---exploratory-data-analysis-eda-

Lending companies often struggle with lending decisions due to applicants with insufficient credit history. This can lead to defaults. This case study performed Exploratory Data Analysis (EDA) on a loan application dataset to understand patterns and minimize loan defaults while ensuring deserving applicants are not rejected.

machine-learning-for-solar-energy-prediction

Predict the Power Production of a solar panel farm from Weather Measurements using Machine Learning

machine-learning-model-for-solar-energy-forecast

basic machine learning

mlproject

multiple-linear-regression-bike-share-demand-prediction

BoomBikes, a US-based bike-sharing provider, aims to forecast the post-quarantine demand for shared bikes in the American market using multiple linear regression analysis. The primary goal is to identify the significant variables influencing bike demand and gauge their predictive power.

named-entity-recognition-in-healthcare-data

This repository hosts the "Medical NER" project, focusing on Named Entity Recognition (NER) in healthcare text. It aims to extract disease names and treatments from medical data, aiding comprehension for non-medical professionals and enabling data-driven insights in the healthcare industry.

neuralforecast-timellm

Scalable and user friendly neural :brain: forecasting algorithms.

patchtst

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

sentiment-based-product-recommendation-system

This project aims to develop a sentiment-based product recommendation system for e-commerce. By analyzing user reviews and ratings, it provides personalized product suggestions. Deployed with a user-friendly interface, it enhances the shopping experience and boosts sales for the company.

solar-power-datasets-and-resources

Resources about solar power systems for data science

telecom-churn-predictor---different-models-approach

"Telecom Churn Predictor" project, which employs a diverse range of predictive models to tackle the challenge of customer churn in the telecommunications industry.High customer churn rates pose a significant threat to telecom companies. To address , I explored various machine learning models to predict which customers are at a high risk of churning

time-series-analysis--reprogram--project

Collection of notebooks for time series analysis

time-series-library

A Library for Advanced Deep Time Series Models.