Pinned Repositories
CryptoTradingBot
My completed project for a Crypto Trading Bot, which can make decisions whether to buy or sell a set of cryptocurrencies. A sample data is included in the repo, which shows that the bot is able to make a profit (explained in my pdf report in the repo).
DeepLearningTensorFlow
Deep Learning using TensorFlow: Predicting Heart Disease Presence From Medical Records. This project aims to predict the presence of heart disease in individuals using machine learning techniques.
DjangoRestAPI
This project involves the implmenetation of REST API endpoints for bioscience researchers working on protein domains. The API allows the researchers to regularly query for the data they've generated. The API endpoints specification and data are explained further in below sections.
DJApp
My completed project for a DJ App using C++ with JUCE. My repo includes an mp4 video that showing the user how to use the DJ App and also a report explaining the code.
frontendVanillaJavascript
My completed project for a simple website (HTML, CSS, vanilla JavaScript) for a financial magazine.
login10xyme
MyCryptoReactNative
Crypto Trading simulation app. The app allows users to simulate crypto trading such as adding funds to the crypto wallet, buying and selling the desired currencies and has access to a portfolio.
NodeJSDevices
This project is a backend logic for a dynamic web application which allows users to monitor and control devices in their smart home. The app is just a prototype so it doesn’t need interface with actual hardware, but it should provide the necessary functionality
PythonNumpyPandas
Using Python and the Pandas and Numpy libraries to analyse the changes in foreign investor sentiment towards the UK after the Brexit vote in 2016.
UnsupervisedLearning
Conducting a comparative analysis of two similar clustering algorithms - K-means clustering and hierachical clustering, in order to identify high-risk diabetic patients. The aim is to examine how accurately these algorithms are able to segment patient data into meaningful clusters.
jumanlee's Repositories
jumanlee/CryptoTradingBot
My completed project for a Crypto Trading Bot, which can make decisions whether to buy or sell a set of cryptocurrencies. A sample data is included in the repo, which shows that the bot is able to make a profit (explained in my pdf report in the repo).
jumanlee/DeepLearningTensorFlow
Deep Learning using TensorFlow: Predicting Heart Disease Presence From Medical Records. This project aims to predict the presence of heart disease in individuals using machine learning techniques.
jumanlee/DjangoRestAPI
This project involves the implmenetation of REST API endpoints for bioscience researchers working on protein domains. The API allows the researchers to regularly query for the data they've generated. The API endpoints specification and data are explained further in below sections.
jumanlee/DJApp
My completed project for a DJ App using C++ with JUCE. My repo includes an mp4 video that showing the user how to use the DJ App and also a report explaining the code.
jumanlee/frontendVanillaJavascript
My completed project for a simple website (HTML, CSS, vanilla JavaScript) for a financial magazine.
jumanlee/login10xyme
jumanlee/MyCryptoReactNative
Crypto Trading simulation app. The app allows users to simulate crypto trading such as adding funds to the crypto wallet, buying and selling the desired currencies and has access to a portfolio.
jumanlee/NodeJSDevices
This project is a backend logic for a dynamic web application which allows users to monitor and control devices in their smart home. The app is just a prototype so it doesn’t need interface with actual hardware, but it should provide the necessary functionality
jumanlee/PythonNumpyPandas
Using Python and the Pandas and Numpy libraries to analyse the changes in foreign investor sentiment towards the UK after the Brexit vote in 2016.
jumanlee/UnsupervisedLearning
Conducting a comparative analysis of two similar clustering algorithms - K-means clustering and hierachical clustering, in order to identify high-risk diabetic patients. The aim is to examine how accurately these algorithms are able to segment patient data into meaningful clusters.