Pinned Repositories
AI-Agents-For-Reanalysis-of-Risk-Tolerance
Reanalyze Risk Tolerance Using AI Agentic Workflow: This project leverages AI agents and advanced language models to reevaluate user risk tolerance based on financial data and demographic information extracted from JSON files. Utilizing Microsoft Autogen and Llama3.1 8b from Groq API.
Applied-Data-Science-Capstone-project
IBM Data Science Applied Capstone Project (on SpaceX data Set): To predict whether first stage of the rocket will Land or not
Assistant_with_V-A
CC_Fraud-Detection-Project-for-AFAME-TECHNOLOGIES
Credit Card Fraud Detection: An ML project on credit card fraud detection using various ML techniques to classify transactions as fraudulent or legitimate. This project involves data analysis, preparation, and use of models like Logistic regression, KNN, Decision Trees, Random Forest, XGBoost, and SVM, along with various oversampling technique.
Estimation-of-acoustic-impedance-from-seismic-data-using-temporal-convolutional-network
The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG Technical Program Expanded Abstracts, 2019.
faultSeg
Using synthetic datasets to train an end-to-end CNN for 3D fault segmentation (We are working on an improved version!)
Formation_Evaluation_and_Well_Log_Analysis-Case_Study
Comprehensive analysis and evaluation of well log data for subsurface reservoir characterization. Includes gamma ray tool design, quality control of wireline logs, porosity, permeability, and water saturation calculations using advanced petrophysical methods. Features machine learning models for lithofacies classification and case study.
imtej-Seismic-FaultNet-Fault-Segmentaion-with-U-Net-Architecture-
Seismic FaultNet is a project focused on 3D seismic fault segmentation using synthetic datasets. It implements a U-Net based convolutional neural network (CNN) trained on 200 pairs of synthetic seismic and fault volumes. The study evaluates segmentation performance using precision-recall and ROC
Lithofacies-Classification-using-ML-Techniques
Lithofacies classification using well log data from the Hugoton and Panoma Fields dataset. This project implements various machine learning algorithms including Support Vector Machines, Random Forest, Neural Networks, and others to predict facies groups. The study focuses on improving facies classification accuracy using well log data from 9 well.
manim
Animation engine for explanatory math videos
imtej's Repositories
imtej/AI-Agents-For-Reanalysis-of-Risk-Tolerance
Reanalyze Risk Tolerance Using AI Agentic Workflow: This project leverages AI agents and advanced language models to reevaluate user risk tolerance based on financial data and demographic information extracted from JSON files. Utilizing Microsoft Autogen and Llama3.1 8b from Groq API.
imtej/Lithofacies-Classification-using-ML-Techniques
Lithofacies classification using well log data from the Hugoton and Panoma Fields dataset. This project implements various machine learning algorithms including Support Vector Machines, Random Forest, Neural Networks, and others to predict facies groups. The study focuses on improving facies classification accuracy using well log data from 9 well.
imtej/Applied-Data-Science-Capstone-project
IBM Data Science Applied Capstone Project (on SpaceX data Set): To predict whether first stage of the rocket will Land or not
imtej/Assistant_with_V-A
imtej/CC_Fraud-Detection-Project-for-AFAME-TECHNOLOGIES
Credit Card Fraud Detection: An ML project on credit card fraud detection using various ML techniques to classify transactions as fraudulent or legitimate. This project involves data analysis, preparation, and use of models like Logistic regression, KNN, Decision Trees, Random Forest, XGBoost, and SVM, along with various oversampling technique.
imtej/Estimation-of-acoustic-impedance-from-seismic-data-using-temporal-convolutional-network
The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG Technical Program Expanded Abstracts, 2019.
imtej/faultSeg
Using synthetic datasets to train an end-to-end CNN for 3D fault segmentation (We are working on an improved version!)
imtej/Formation_Evaluation_and_Well_Log_Analysis-Case_Study
Comprehensive analysis and evaluation of well log data for subsurface reservoir characterization. Includes gamma ray tool design, quality control of wireline logs, porosity, permeability, and water saturation calculations using advanced petrophysical methods. Features machine learning models for lithofacies classification and case study.
imtej/imtej-Seismic-FaultNet-Fault-Segmentaion-with-U-Net-Architecture-
Seismic FaultNet is a project focused on 3D seismic fault segmentation using synthetic datasets. It implements a U-Net based convolutional neural network (CNN) trained on 200 pairs of synthetic seismic and fault volumes. The study evaluates segmentation performance using precision-recall and ROC
imtej/manim
Animation engine for explanatory math videos
imtej/ML_Project
Students Performance Prediction(Regression Models). The goal is to predict `Maths Score` of a given student provided various features (Regression Analysis). Insipration is to understand the influence of the parents background, test preparation etc on students performance.
imtej/Recommendation-System-For-Books
Recommendation System for Books using Collaborative Filterings: An ML Project to Recommend 'n' similar Books for a given book, as per the Collaborative users' ratings of the books. This Project also involves the deployment in a Flask Based web application.
imtej/SpaceX_Landing_Analysis_Prediction_Project1
IBM Data Science Applied Capstone Project (on SpaceX data Set): To predict whether first stage of the rocket will Land or not
imtej/Stock-Trend-and-Price-Prediction-using-DL
Stock Trend and Price Prediction using Deep Learning Model (Using a sequence Model "LSTM: Long Short Term Memory Network")