Daniel has successfully architected, developed and deployed several websites and APIs with Django/Flask frameworks. In the process, becoming familiar with; CSS3, HTML5, object-relational mapping, web servers, form handling, caching and Cloud platforms.
Daniel routinely architects and constructs complex data pipelines. Pulled data from dozens of websites, is capabale of analyzing and manipulating a diverse range of data formats. In addition, highly experienced with the visualizing data.
Daniel has successfully trained a series of supervised machine learning supervised models including; object detection, computer vision, logistic regression, text classification and random forests. He has developed a liking to feature engineering, optimization and model tuning.
Building a hackernews app with React and Hackernews API.
API React.js Redux.js Javascript
Building a cryptocurrency app with React and CoinGecko API.
API React.js Redux.js Javascript Chart.js
Building a real-time chat application with socket.io and Nodejs.
Nodejs Express.js socket.io
Building a full-stack, bidding platform app for company stock.
Heroku Django Materialize Javascript Chart.js SQL
Building a lyrics application, powered by musixmatch API.
React.js Github Pages Javascript HTML/CSS JSON API
Developing a web-based dashboard using purely open source libraries, based on the Carbon Intensity API.
React.js Github Pages Javascript HTML/CSS JSON API Chart.js
Developing a front-end application for a grocery store in React.
React.js Github Pages Javascript HTML/CSS JSON
Architecting and deploying a polling themed web application.
Pythonanywhere Django sqlite Python
Preparing data for, and training a RetinaNet object detection model for sea turtles.
RetinaNet Python Google Collab keras
Building a forum web application populated by a fictional robot community.
Heroku Python SQL Flask
Building a machine learning model to predict rain on the next day (with 86% accuracy).
sklearn Python jupyter
Building a machine learning model to automatically classify spam sms messages (with 96% accuracy).
sklearn python jupyter
Using sklearn to predict sentiment from IMDB's movie review dataset (with 81% accuracy).
sklearn python jupyter
Building a computer vision model to detect pools from satellite imagery.
opencv2 python jupyter
Training a YOLOv3 model to detect sharks inside image/video formats.
cuda c++ CNN YOLOv3
Architecting, building and deploying a lightweight visualization web application.
Flask Heroku python pygal
Training a YOLOv3 model to detect National Fire Protection Association (NFPA) symbols.
cuda c++ CNN YOLOv3
Building and deploying animated visualizations for highly hierarchical data.
tableau desktop tableau public D3.js python
Collection of several logistic regression (binary classification) models, mainly using health data.
jupyter notebook sklearn pandas python seaborn
Building a comprehensive data profiler in python.
jupyter notebook pandas python seaborn
Generating a static album website from an unknown amount of data.
python jupyter
A tableau dashboard which examines over a decade of crash data in Victoria.
tableau desktop tableau public python
A series of tableau dashboards which examine over a decade of crime data in Victoria.
tableau desktop tableau public python
Designing, coding and compiling an education themed windows desktop application. This project has 2 parts.
Visual Studio C#