Neill-Erasmus

2024-Sproutopia

ad-selection

Using upper confidence bound reinforcement learning to determine the most effective advert in a dataset.

advertising-budgets-and-sales-regression

Created a multiple linear regression model to predict business sales returns, utilizing data from TV, radio, and newspaper advertising budgets. The model aids in optimizing advertising strategies for enhanced return on investment.

ai-generated-art

I created and trained a DCGAN (Deep Convolutional Generative Adversarial Network) to produce artificial portraits using a dataset containing more than 6000 images.

diabetes-classification

An artificial neural network-based model for diabetes prediction, leveraging machine learning techniques to analyze relevant health data and provide accurate predictions regarding the likelihood of diabetes.

file-cleanup-automation

A python script to automate the cleanup of junk files on your Windows system.

kung-fu

I utilized the A3C (Asynchronous Advantage Actor-Critic) algorithm to train a Deep Q-Learning (DQN) model, specifically tailored to solve the Kungfu gym environment.

lunar-lander

Trained a Deep Q-Learning agent to autonomously land a lunar module in OpenAI's Gymnasium Lunar Lander environment.

pacman

I developed and trained a deep convolutional Q-learning model to enable an agent to successfully solve the Pacman gym environment.

sugarcane-leaf-disease-detection

I developed and trained a convolutional neural network (CNN) to recognize diseases in sugarcane by analyzing images of the leaves.

Neill-Erasmus/ai-generated-art

I created and trained a DCGAN (Deep Convolutional Generative Adversarial Network) to produce artificial portraits using a dataset containing more than 6000 images.

Neill-Erasmus/file-cleanup-automation

A python script to automate the cleanup of junk files on your Windows system.

Neill-Erasmus/2024-Sproutopia

Neill-Erasmus/ad-selection

Using upper confidence bound reinforcement learning to determine the most effective advert in a dataset.

Neill-Erasmus/advertising-budgets-and-sales-regression

Created a multiple linear regression model to predict business sales returns, utilizing data from TV, radio, and newspaper advertising budgets. The model aids in optimizing advertising strategies for enhanced return on investment.

Neill-Erasmus/chrome-dino-automated

A python script to automate the chrome dino game.

Neill-Erasmus/credit-card-fraud

Using a self organizing map (SOM) to identify frauds in the credit card application process.

Neill-Erasmus/customer-personality-analysis

Leveraging K-Means clustering for insightful customer segmentation, enabling businesses to tailor products to specific customer types.

Neill-Erasmus/diabetes-classification

An artificial neural network-based model for diabetes prediction, leveraging machine learning techniques to analyze relevant health data and provide accurate predictions regarding the likelihood of diabetes.

Neill-Erasmus/keras

Deep Learning for humans

Neill-Erasmus/kung-fu

I utilized the A3C (Asynchronous Advantage Actor-Critic) algorithm to train a Deep Q-Learning (DQN) model, specifically tailored to solve the Kungfu gym environment.

Neill-Erasmus/lunar-lander

Trained a Deep Q-Learning agent to autonomously land a lunar module in OpenAI's Gymnasium Lunar Lander environment.

Neill-Erasmus/pacman

I developed and trained a deep convolutional Q-learning model to enable an agent to successfully solve the Pacman gym environment.

Neill-Erasmus/study-hours-regression

Utilizing simple linear regression to forecast students' academic performance by analyzing the correlation between study hours and exam marks.

Neill-Erasmus/sugarcane-leaf-disease-detection

I developed and trained a convolutional neural network (CNN) to recognize diseases in sugarcane by analyzing images of the leaves.

Neill-Erasmus/gender-classification

Comparing different classification models on the same dataset to classify people into genders based on several features.

Neill-Erasmus/market-basket-optimization

Using the apriori association rule learning algorithm to identify goods commonly associated and purchased together.

Neill-Erasmus/Neill-Erasmus

Config files for my GitHub profile.

Neill-Erasmus/opencv

Open Source Computer Vision Library

Neill-Erasmus/pdf-to-audiobook

A python script that generates a short story and saves it in PDF format, before rendering an audio version and saving it as an MP3 file.

Neill-Erasmus/pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Neill-Erasmus/restaurant-reviews

I trained a natural language processing (NLP) model to classify restaurant reviews as either positive or negative sentiment.

Neill-Erasmus/scikit-learn

scikit-learn: machine learning in Python

Neill-Erasmus/stock-price-prediction

This project employs LSTM, a type of recurrent neural network, to forecast stock market indices using historical data with features like date, open, high, low, close, and volume. By training the model on this dataset, it learns patterns to predict future market trends, aiding investors, traders, and analysts in decision-making.

Neill-Erasmus/tensorflow

An Open Source Machine Learning Framework for Everyone

Neill-Erasmus/text-to-morse-code

A simple Python application that converts text to Morse code.

Neill-Erasmus/tic-tac-toe

A text based version of the classic tic tac toe game in Python.