Jay Chakalasiya

Stock-Market-Prediction-And-Feature-selection. This project deals with the use of machine learning to predict changes in stock values as well as we incorporating study on effect of different feature selection in our results, as well as we are introducing the non traditional features like Date with specific mapping function and many stock market anomalies

Global-Wheat-Detction-Kaggle-2020. For the Kaggle Competition on object detection with same name. 1) models used are DETR, EfficientDet, YOLOv5, RetinaNet, FasterRCNN. 2) Ensemble inference using Weighted Box Fusion 3) Pseudo Learning to deal with smaller labeled datasets. 4) Mixup as an augmentation technique

iMaterialist-Fashion-2020-at-FGVC7. For Kaggle Competition

Document-Classification. Classification of documents using Naive-Bayes, KNN, Neural Network and Clustering,

Osseus-Fracture-Detection-App. Fracture detection using acoustic response

spyroweb. Jupyter Notebook

Kaggle-Peking-University-Baidu---Autonomous-Driving. For the Kaggle Competition https://www.kaggle.com/c/pku-autonomous-driving