Pinned Repositories
ByteTrack
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
default_bank
The loan_data data frame contains information on 3-year loans that were originated in 2013 by a local bank for customers residing in the United States. The company is looking to see if it can determine the factors that lead to loan default and whether it can predict if a customer will eventually default on their loan at time of loan origination. The goal is to become better at identifying customers at risk of defaulting on their loans to minimize the bank’s financial losses. The data set contains a mixture of applicant demographics (gender, age, residence, etc..), financial information (income, debt ratios, FICO scores, etc..), and applicant behavior (number of open accounts, historical engagement with the bank’s products, number of missed payments, etc. . . ) Exploratory Data Analysis is conducted to examine the data and explore possible important variables. Variable Importance is determined by creating a Gini Index using the varImpPlot() function in Random Forest. After variables are selected, three different models are fit on the training data set including Random Forest, Decision Trees, and K-Nearest Neighbor. The models are then used on the test data set, and a recommendation is given to the bank through an analysis of F1 scores and false negative rates.
Grounded-SAM-2
Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2
Kannada_MNIST_CONV2d
Classifying handwritten digits using a Convolutional Neural Network and Data Augmentation
LOCO-YOLOv8
Using YOLOv8, ByteTrack, and Supervision to detect Logistics Objects in Context (LOCO)
nerfstudio
A collaboration friendly studio for NeRFs
shoe-splatter
titanic_dt
Predicting Titanic survival rates using a Decision Tree Classifier and a Randomized Search Cross Validation
VideoCaptioningWithBLIP
ViTB16-Clustering
tsugg's Repositories
tsugg/default_bank
The loan_data data frame contains information on 3-year loans that were originated in 2013 by a local bank for customers residing in the United States. The company is looking to see if it can determine the factors that lead to loan default and whether it can predict if a customer will eventually default on their loan at time of loan origination. The goal is to become better at identifying customers at risk of defaulting on their loans to minimize the bank’s financial losses. The data set contains a mixture of applicant demographics (gender, age, residence, etc..), financial information (income, debt ratios, FICO scores, etc..), and applicant behavior (number of open accounts, historical engagement with the bank’s products, number of missed payments, etc. . . ) Exploratory Data Analysis is conducted to examine the data and explore possible important variables. Variable Importance is determined by creating a Gini Index using the varImpPlot() function in Random Forest. After variables are selected, three different models are fit on the training data set including Random Forest, Decision Trees, and K-Nearest Neighbor. The models are then used on the test data set, and a recommendation is given to the bank through an analysis of F1 scores and false negative rates.
tsugg/LOCO-YOLOv8
Using YOLOv8, ByteTrack, and Supervision to detect Logistics Objects in Context (LOCO)
tsugg/titanic_dt
Predicting Titanic survival rates using a Decision Tree Classifier and a Randomized Search Cross Validation
tsugg/ByteTrack
[ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
tsugg/Grounded-SAM-2
Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2
tsugg/Kannada_MNIST_CONV2d
Classifying handwritten digits using a Convolutional Neural Network and Data Augmentation
tsugg/nerfstudio
A collaboration friendly studio for NeRFs
tsugg/shoe-splatter
tsugg/Sticky-Notes
This is was a 1 day project I did to detect sticky notes on walls and output its content into a .txt file
tsugg/student_PCA
Unsupervised Learning using PCA
tsugg/VideoCaptioningWithBLIP
tsugg/ViTB16-Clustering
tsugg/TrackingAndCaptioning