Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:

Overview

DeepStock

Technical experimentations to beat the stock market using deep learning.

Experimentations

  1. Deep Learning Stock Prediction with Daily News Headline Analysis

    • An attempt to find the correlation between the daily news headlines and DJIA index.
    • More explained in this slide
  2. Automated Trading Bot using Deep Learning

    • Predicting a company's stock price based only on the price history of the company.
    • Recurrent Neural Networks
    • Convolutional Neural Networks
    • Deep Q NetWorks
    • In-progress
  3. Complex Analysis on Stock using Deep Learning

    • Take multiple features into account to predict the value of a company.
    • In-progress
  4. Portfolio Management using Deep Learning

    • Planned
  5. Macro Economics Analysis

    • Currency and Macro-Tracking-ETFs
    • Planned
Owner
Keon
Keon
End-To-End Crowdsourcing

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Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."

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A multi-mode modulator for multi-domain few-shot classification (ICCV)

A multi-mode modulator for multi-domain few-shot classification (ICCV)

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KwaiRec: A Fully-observed Dataset for Recommender Systems (Density: Almost 100%)

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Video Instance Segmentation using Inter-Frame Communication Transformers (NeurIPS 2021)

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Dogs classification with Deep Metric Learning using some popular losses

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Towards Implicit Text-Guided 3D Shape Generation (CVPR2022)

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Wafer Fault Detection using MlOps Integration

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This repo is developed for Strong Baseline For Vehicle Re-Identification in Track 2 Ai-City-2021 Challenges

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Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data

LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn

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Codes for "Template-free Prompt Tuning for Few-shot NER".

EntLM The source codes for EntLM. Dependencies: Cuda 10.1, python 3.6.5 To install the required packages by following commands: $ pip3 install -r requ

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Event-forecasting - Event Forecasting Algorithms With Python

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Constrained Logistic Regression - How to apply specific constraints to logistic regression's coefficients

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Fully Convolutional DenseNets for semantic segmentation.

Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense

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Model Quantization Benchmark

Introduction MQBench is an open-source model quantization toolkit based on PyTorch fx. The envision of MQBench is to provide: SOTA Algorithms. With MQ

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Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022

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Implementation of SiameseXML (ICML 2021)

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Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2

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[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

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Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection

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