Tasnim Niger's Projects
Train, Tune & Deployment of a machine learning project in Azure cloud platform
Explore the importance of model monitoring and its role in ensuring the ongoing performance and reliability of machine learning models. Conduct long-term model monitoring checks like data drift, target checks, Kolmogorov-Smirnov test, and model drift for sustained model performance assessment.
MLOps principles, utilize version control and CI/CD workflows with GitHub Actions and successfully deploy ML projects in Azure ML, ensuring streamlined and automated ML development workflows.
A classification model to predict clients who are likely to default on their loan and give recommendations to the bank on the important features to consider while approving a loan.
This repository has been created as project work of the Data Science and AI Internship program by Bytes of Intelligence, showcasing my commitment to the program.
The code provided is designed to detect pneumonia from chest X-ray images using a Convolutional Neural Network (CNN) implemented in TensorFlow Keras.
Main focus of this repository is Exploratory data analysis (EDA), Data Visualization and Statistical analysis
A machine learning model that can identify fake news articles.
A Generative AI application using a Large Language Model to automate the classification and processing of support tickets.
This problem statement is based on the Shinkansen Bullet Train in Japan, and passengers’ experience with that mode of travel. This machine learning exercise aims to determine the relative importance of each parameter about their contribution to the passengers’ overall travel experience.
Identify Lung Cancer from CT-Scan images using Identity Block in ResNets like architecture
This repository contains the code and data for cutting-edge research aimed at identifying the thought patterns of patients with psychotic disorders.
A Generative AI solution using the LangChain framework and a Large Language Model to automate tasks pertaining to Data Analysis, Data Science, Database Querying and Retrieval-Augmented Generation.
Applied MobileNetV2 pretrained model for Leaf disease classification using TensorFlow Library
An online education company was trying to convert their customers (lead) to paid customers. Analyze and build an ML model to identify which leads are more likely to convert to paid customers.
All NLP related necessary python projects