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WebClinic's Projects

smartimport icon smartimport

An unsupervised analysis combining topic modeling, clustering, cosine similrity, and word2vec to provide recommendations of python packages to use in your project based on your README.md file and README.md files of those found in Github

smartpipeline icon smartpipeline

A framework for rapid development of robust data pipelines following a simple design pattern

smartporfolio icon smartporfolio

Using the Effiecient Frontier from Finaquant to reallocate stocks

smartspread icon smartspread

The Codes and Scripts used for the Smart Spread algorithm.

smartstocks icon smartstocks

Smart Stocks is Stock Application created using Django Framework

smarttradingbot icon smarttradingbot

Application of reinforcement learning to automated stock and cryptocurrency trading. QLEARNING YFINANCE

smc-web icon smc-web

This project is a front end code of stock marketing charting practice with angular.

smd-invest-pwa icon smd-invest-pwa

A progress web app implemented in flutter for SMD Global Investments.

smp-20 icon smp-20

SMP-20(A Stock Market Analysis Project -College Minor Project )The major components of this project’s architecture include- 1. Historical data analysis deep learning model. 2. Sentimental analysis machine learning model 3. Firebase to store the output of the model 4. A computer server running the models periodically 5. User interface using flutter

smtm icon smtm

It's a game to get money

smu_capstoneproject_comparisonwebsite icon smu_capstoneproject_comparisonwebsite

A comparison platform (think Seedly, Moneysmart and Nerdwallet) on the different shariah-compliant financial products, and where users can leave, read, update reviews. Admin has the right to delete the reviews.

smu_capstoneproject_roboadvisorapp icon smu_capstoneproject_roboadvisorapp

A shariah-compliant roboadvisor mobile app that allows users to create portfolios, add/withdraw funds. They can also access the learning resources from the app.

snoopy icon snoopy

System to perform a feasibility study for ML before developing costly machine learning models.

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