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Neil Pandya's Projects

anomalydetection icon anomalydetection

This repository is part of an article about how to forecast and detect anomalies on time-series data. The main objective is to train a RNN regressor on the Bitcoin dataset to predict future values on then detect anomalies in the whole data window - that last step achieved by implementing a RNN Autoencoder. You'll see some other models in the notebooks that I've provided to you in case they are of your interest and this RNN regressor + RNN Autoencoder doesn't perform well for your purpose in any other scenario. The dataset used is available at https://www.kaggle.com/mczielinski/bitcoin-historical-data and contains BITCOIN/USD 1-minute candle data, from 2012-01-01 to 2020-12-31. I hope you can get advantage of this approach!

darknet icon darknet

Neil Pandya's Rendition of YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet)

mask_rcnn icon mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

rogauracore_gui icon rogauracore_gui

GUI wrapper for rogauracore used to control RGB keyboards in asus ROG laptops

super-gradients icon super-gradients

Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.

tensorflow-yolov4-tflite icon tensorflow-yolov4-tflite

YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite

threejsdonuts icon threejsdonuts

An example site using vite to play with ThreeJS and lil-gui.

trainingdatagenerator icon trainingdatagenerator

For machine learningpurposes, python script creates circles with bounding boxes, and accompanying annotations in the PASCAL VOC 2007 format. Intended for use with darkflow

yolov9 icon yolov9

Neil Pandya's implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

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