Warren - Stock Price Predictor

Overview

Warren - Stock Price Predictor

Codacy Badge GitHub GitHub code size in bytes GitHub repo size GitHub language count GitHub last commit

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. The efficient-market hypothesis suggests that stock prices reflect all currently available information and any price changes that are not based on newly revealed information thus are inherently unpredictable. Others disagree and those with this viewpoint possess myriad methods and technologies which purportedly allow them to gain future price information.

We make use of Facebook's Time Series forcasting algorithm Prophet to predict stock market price of US based companies in real time using multi-variate, single step forecasting strategy.

Header

Getting Started

Download or clone project from github:

$ git clone https://github.com/nityansuman/warren.git

Create a project environment (Anaconda recommended):

$ conda create --name envname python
$ conda activate envname

Install prerequisites:

$ pip install -r REQUIREMENTS.txt

Run project:

$ cd warren
$ python runserver.py

Model Validation Analysis

Facebook (Stock: FB) Validation FB_validation

Microsoft (Stock: MSFT) Validation MSFT_validation

Google (Stock: GOOGL) Validation GOOGLE_validation

Support

If you like the work I do, show your appreciation by 'FORK', 'STAR' and 'SHARE'.

forthebadge made-with-python Forthebadge

Owner
Kumar Nityan Suman
Senior Data Scientist, AI Researcher. Machine Learning and Deep Learning with Python.
Kumar Nityan Suman
LinearRegression2 Tvads and CarSales

LinearRegression2_Tvads_and_CarSales This project infers the insight that how the TV ads for cars and car Sales are being linked with each other. It i

Ashish Kumar Yadav 1 Dec 29, 2021
Predicting job salaries from ads - a Kaggle competition

Predicting job salaries from ads - a Kaggle competition

Zygmunt Zając 57 Oct 23, 2020
Binary Classification Problem with Machine Learning

Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl

Dinesh Mali 0 Jan 20, 2022
Data Efficient Decision Making

Data Efficient Decision Making

Microsoft 197 Jan 06, 2023
A Software Framework for Neuromorphic Computing

A Software Framework for Neuromorphic Computing

Lava 338 Dec 26, 2022
Climin is a Python package for optimization, heavily biased to machine learning scenarios

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Biomimetic Robotics and Machine Learning at Technische Universität München 177 Sep 02, 2022
A simple application that calculates the probability distribution of a normal distribution

probability-density-function General info An application that calculates the probability density and cumulative distribution of a normal distribution

1 Oct 25, 2022
Test symmetries with sklearn decision tree models

Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro

Rupert Tombs 2 Jul 19, 2022
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l

Distributed (Deep) Machine Learning Community 23.6k Jan 03, 2023
fastFM: A Library for Factorization Machines

Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat

1k Dec 24, 2022
a distributed deep learning platform

Apache SINGA Distributed deep learning system http://singa.apache.org Quick Start Installation Examples Issues JIRA tickets Code Analysis: Mailing Lis

The Apache Software Foundation 2.7k Jan 05, 2023
Both social media sentiment and stock market data are crucial for stock price prediction

Relating-Social-Media-to-Stock-Movement-Public - We explore the application of Machine Learning for predicting the return of the stock by using the information of stock returns. A trading strategy ba

Vishal Singh Parmar 15 Oct 29, 2022
This repository demonstrates the usage of hover to understand and supervise a machine learning task.

Hover Example Apps (works out-of-the-box on Binder) This repository demonstrates the usage of hover to understand and supervise a machine learning tas

Pavel 43 Dec 03, 2021
Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations.

BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer

KTH Mechanics 8 Mar 31, 2022
InfiniteBoost: building infinite ensembles with gradient descent

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

Alex Rogozhnikov 183 Jan 03, 2023
🎛 Distributed machine learning made simple.

🎛 lazycluster Distributed machine learning made simple. Use your preferred distributed ML framework like a lazy engineer. Getting Started • Highlight

Machine Learning Tooling 44 Nov 27, 2022
Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters

Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing

Peter Wittek 239 Nov 10, 2022
Dieses Projekt ermöglicht es den Smartmeter der EVN (Netz Niederösterreich) über die Kundenschnittstelle auszulesen.

SmartMeterEVN Dieses Projekt ermöglicht es den Smartmeter der EVN (Netz Niederösterreich) über die Kundenschnittstelle auszulesen. Smart Meter werden

greenMike 43 Dec 04, 2022
Timeseries analysis for neuroscience data

=================================================== Nitime: timeseries analysis for neuroscience data ===============================================

NIPY developers 212 Dec 09, 2022
Predict profitability of trades based on indicator buy / sell signals

Predict profitability of trades based on indicator buy / sell signals Trade profitability analysis for trades based on various indicators signals: MAC

Tomasz Porzycki 1 Dec 15, 2021