Jason's starred repositories
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Sequence-Level-Semantics-Aggregation
Sequence Level Semantics Aggregation for Video Object Detection
mega.pytorch
Memory Enhanced Global-Local Aggregation for Video Object Detection, CVPR2020
wikipedia-data-science
Working with and analyzing Wikipedia Data
PyTorch-YOLOv3
Minimal PyTorch implementation of YOLOv3
davis2017-evaluation
Evaluation Framework for DAVIS 2017 Semi-supervised and Unsupervised used in the DAVIS Challenges
NeosegPipeline
This tool allows segmentin brain MRI using a multi-atlas based approach either via joint label fusion (ANTS) or via generating a subject-specific atlas.
Life-long-Learner
Personal Notes About Everything.
sobolev_gan
Pytorch implemention of Sobolev GAN (https://arxiv.org/abs/1711.04894)
tf-library
A (growing) collection of useful abstractions and implementations for research.
lstm-oreilly
How to build a Multilayered LSTM Network to infer Stock Market sentiment from social conversation using TensorFlow.
image-segmentation-keras
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
3D-brain-segmentation
This is a repository containing code to Paper "Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation" published at MDPI Applied sciences journal - https://www.mdpi.com/2076-3417/9/3/404 .