yujansaya

a3c_agent_pytorch

This code implements an Asynchronous Advantage Actor-Critic (A3C) algorithm using PyTorch to train an agent to play the Atari game "Boxing"

ai_math_solver

The project deploys a pre-trained language model to efficiently solve mathematical problems by generating textual answers based on input questions. It enhances performance with optimizations like quantization and extracts numerical answers from the generated text.

credit_risk_model

Create a model to predict which clients are more likely to default on their loans.

diarization_sentiment_analyse

A web app for real-time transcription, speaker diarization, and sentiment analysis

gemma

Google – AI Assistants for Data Tasks with Gemma

gemma_prompt_recovery

The project aims to generate prompts for essay rewriting by fine-tuning the Gemma model on a dataset of original and rewritten texts, integrating LoRA for efficient training and inference. Tools: Python, Hugging Face's Transformers and Datasets, Gemma, LoRA, Accelerate, PyTorch, Pandas.

harmful_brain_acitivity

Harmful Brain Activity Detection Classification - Classify seizures and other patterns of harmful brain activity in critically ill patients

house_price_prediction

House Price Prediction (Kaggle)

kaggle_fraud_detection

Credit Card Fraud Detection

molecule_binding_prediction

The project utilises ML models and ensembles to predict molecular binding, leveraging fingerprints and protein features. It evaluates model performance, integrates calibration for refined predictions, and aims to optimise accuracy in chemical compound interactions. Tools: DuckDB, RDKit, XGBoost, CatBoost, LightGBM, Ensemble Learning,Calibration

yujansaya/harmful_brain_acitivity

Harmful Brain Activity Detection Classification - Classify seizures and other patterns of harmful brain activity in critically ill patients

yujansaya/a3c_agent_pytorch

This code implements an Asynchronous Advantage Actor-Critic (A3C) algorithm using PyTorch to train an agent to play the Atari game "Boxing"

yujansaya/ai_math_solver

The project deploys a pre-trained language model to efficiently solve mathematical problems by generating textual answers based on input questions. It enhances performance with optimizations like quantization and extracts numerical answers from the generated text.

yujansaya/credit_risk_model

Create a model to predict which clients are more likely to default on their loans.

yujansaya/diarization_sentiment_analyse

A web app for real-time transcription, speaker diarization, and sentiment analysis

yujansaya/gemma

Google – AI Assistants for Data Tasks with Gemma

yujansaya/gemma_prompt_recovery

The project aims to generate prompts for essay rewriting by fine-tuning the Gemma model on a dataset of original and rewritten texts, integrating LoRA for efficient training and inference. Tools: Python, Hugging Face's Transformers and Datasets, Gemma, LoRA, Accelerate, PyTorch, Pandas.

yujansaya/house_price_prediction

House Price Prediction (Kaggle)

yujansaya/kaggle_customer_segmentation

Mall Customer Segmentation Data

yujansaya/kaggle_fraud_detection

Credit Card Fraud Detection

yujansaya/kaggle_titanic

Machine learning to predict which passengers survived the Titanic shipwreck

yujansaya/molecule_binding_prediction

The project utilises ML models and ensembles to predict molecular binding, leveraging fingerprints and protein features. It evaluates model performance, integrates calibration for refined predictions, and aims to optimise accuracy in chemical compound interactions. Tools: DuckDB, RDKit, XGBoost, CatBoost, LightGBM, Ensemble Learning,Calibration

yujansaya/raha_beach_ocr

OCR Technical Assignment

yujansaya/yujansaya