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An abstract implementation of a Multilayered Perceptron (Multilayered Feedforward Neural Network). Provides a well-documented API which exposes a wrapper around the whole process (all the way from network config, to modelling, to training and predicting). Built in Python.

Python 100.00%
backpropagation feedforward-neural-network gradient-descent linear-function machine-learning neural-network perceptron sigmoid-function

multilayerperceptronfnn's Introduction

Hey there ๐Ÿ‘‹

I am a Computer Science with Year in Industry graduate always on the lookout for new opportunities to learn and develop new skills.

Currently, I am a Software Engineer at X-Lab Systems working on the Labgnostic digital diagnostic exchange solution.

I am developing full stack projects & taking an active interest in distributed systems, Cloud infrastructure and machine learning.

My final year project in University was on building a modular and scalable benchmarking tool for various Blockchain networks and smart contract applications (i.e Ethereum, Stellar, Tron, RSK, etc.) and performing an analysis on the generated data.

This GitHub page serves as an observation point for my software engineering path and development. ๐ŸŒŸ

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Project Highlights

Fun silly little projects I started

and never properly finished...

ZRD ๐Ÿช™

cete-api ๐Ÿฌ, cete-api-infrastructure ๐Ÿข

bisMate ๐Ÿ’ผ

Academic Work

  1. Gradient boosted machine learning model to predict H2, CH4 and CO2 uptake in metal organic frameworks using experimental data (ci-2022-01240s) - Contributor

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