Our Projects

Projects found: 87

Actor-Critic CartPole

Reinforcement learning implementation of an Actor-Critic model applied to the CartPole environment.

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Adversarial Attacks (Modified)

Modified version of adversarial attack techniques with new metrics and visualizations.

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Adversarial Attacks on Neural Networks

Explores adversarial vulnerabilities in deep learning models and attack techniques.

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Arrays and Vectors with NumPy

Python script demonstrating array and vector manipulation using NumPy.

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Assign Adversarial Attacks

Notebook demonstrating assigned adversarial attack scenarios for testing model robustness.

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Attack & Defence - ImageNet v2.5

Updated adversarial attack and defense implementation using ImageNet dataset.

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Attack & Defense with Beagle (ImageNet)

Adversarial model trained using Beagle variation on ImageNet defense strategy.

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Attack and Defence - Beagle Model

Custom Beagle-based architecture for improved defense against adversarial attacks.

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Attack and Defence - ImageNet

Adversarial attack and defense strategy implementation for ImageNet model evaluation.

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Attack and Defence - ImageNet v2.5

Enhanced v2.5 version of attack and defense adversarial model with test metrics.

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Bayesian Classification

Implementation of Bayesian classifiers for probabilistic data modeling and classification.

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Book: Deep Learning

Essential theory and foundation book on deep learning for AI and neural networks.

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Book: Deep Learning

Essential theory and foundation book on deep learning for AI and neural networks.

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Book: Deep Learning with Python (2nd Edition)

Comprehensive book covering practical deep learning with Python and Keras.

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Book: FairML Data 460

PDF reference book discussing fairness and explainability in machine learning.

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Book: FairML Data 460

PDF reference book discussing fairness and explainability in machine learning.

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Book: Hands-On ML with Scikit-Learn, Keras, TensorFlow (3rd Ed.)

Practical guidebook for implementing machine learning pipelines and deep learning models.

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Book: Hands-On ML with Scikit-Learn, Keras, TensorFlow (3rd Ed.)

Practical guidebook for implementing machine learning pipelines and deep learning models.

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Book: Machine Learning with Scikit-Learn, Keras, and TensorFlow

PDF textbook on ML frameworks and how to integrate them in Python workflows.

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Book: Machine Learning with Scikit-Learn, Keras, and TensorFlow

PDF textbook on machine learning frameworks and how to integrate them in Python workflows.

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Book: Projects for The Little SAS Book

EPUB reference book with exercises and projects based on The Little SAS Book.

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Book: Python for Data Analysis (3rd Edition)

EPUB version with the first two chapters of Wes McKinney's Python for Data Analysis.

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Book: The Elements of Statistical Learning (2nd Ed.)

PDF textbook covering statistical learning, classification, and regression in depth.

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Breast Cancer - Colab Version

PDF version of the Colab notebook analyzing breast cancer data.

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Breast Cancer Classification

Builds a supervised ML model for classifying breast cancer using diagnostic features.

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Build a Decision Tree

Basic decision tree construction and evaluation using Python libraries.

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Build a Decision Tree with Python

A step-by-step notebook to build a decision tree classifier in Python.

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Build an XGBoost Model with Python

Train and evaluate an XGBoost model for structured data classification.

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CIFAR-10 Fake Image Analysis (2) - Script

Python script for analyzing fake CIFAR-10 images using NumPy and visualization.

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CIFAR-10 Fake Image Analysis (Notebook)

Jupyter notebook exploring fake image classification and softmax scoring using CIFAR-10.

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CIFAR-10 Fake Image Analysis Script

A standalone script for loading and analyzing generated CIFAR-10 images.

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CIFAR-10 Fake Images Analysis

Script that analyzes generated fake images on the CIFAR-10 dataset using predictions and visualization.

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CIFAR-10 GAN Complete (Original)

Original complete GAN notebook for image generation on CIFAR-10 dataset.

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CIFAR-10 GAN Final

A complete generative adversarial network (GAN) trained on the CIFAR-10 dataset to synthesize realistic images.

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CIFAR10GAN Complete 1

Complete GAN training notebook on CIFAR-10 dataset with additional layers and tweaks.

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CIFAR10GAN Final

Final training implementation of a GAN on CIFAR-10 dataset.

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Chest CT Scan CNN

Deep learning-based model to classify chest CT scans into multiple cancer types using CNNs.

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Chest CT Scan CNN (Original)

Initial CNN implementation for analyzing chest CT scan images.

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Chest Cancer Detection (PDF Report)

Deep learning-based PDF paper for detecting chest cancer from CT scans.

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Construct a Naive Bayes Model

Notebook to construct and test a Naive Bayes classifier from scratch in Python.

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Data Preprocessing - German Dataset

Feature engineering and preprocessing for German credit dataset.

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Decision Tree 1

Single-decision-tree experiment for educational purposes.

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Decision Tree Experiment 1

Early notebook test of decision tree functionality with sample data.

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EMR Glue with PySpark

Data pipeline example using AWS EMR, Glue, and PySpark integration.

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Evaluate Simple Linear Regression

Model evaluation and metric analysis for simple linear regression models.

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Explain a Neural Network Model

Interpretation of neural network layers and output using Python.

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Hypothesis Testing with Python

Perform standard hypothesis testing procedures using Python.

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Hypothesis Testing with Python (2)

Second version of hypothesis testing notebook for comparison and validation.

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Interpret Multiple Regression Results

Statistical interpretation of multiple linear regression output using Python.

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K-Means Clustering

Builds a K-means clustering model in Python to group data points into clusters.

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Logistic Regression

Notebook demonstrating binary classification using logistic regression.

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MLP 440

Multilayer perceptron model notebook for machine learning experimentation.

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MLP Preprocessing Optimization

Optimizing MLP input data using pipeline techniques and visualizations.

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MLP Preprocessing with Plots

Enhanced MLP data preprocessing notebook with step-by-step visualizations.

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Modified CIFAR-10 GAN

Enhanced GAN training notebook on the CIFAR-10 dataset with new architecture tweaks.

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Multiple Linear Regression

Notebook that builds a multiple linear regression model with standard datasets.

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Multiple Linear Regression (Alt)

Alternative implementation of multiple linear regression with visualization options.

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Naive Bayes with Python

Constructs a Naive Bayes classifier with Python for supervised learning tasks.

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One-way vs Two-way ANOVA

Statistical comparison using one-way and two-way ANOVA tests in Python.

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Optimized Data Preprocessing

Performs data preparation and feature engineering using optimized pipelines.

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Optimized Data Preprocessing

Preprocessing pipeline optimization with cross-validation.

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Optimized Preprocessing v2

Updated and expanded version of optimized data preprocessing.

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Perform Feature Engineering

Notebook demonstrating various feature engineering techniques for ML models.

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Perform Feature Engineering

Notebook exploring various feature engineering techniques for machine learning.

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Perform Multiple Linear Regression

Explores multivariate linear regression using various implementation strategies.

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Perform Multiple Linear Regression (Alt)

Alternative notebook implementation for multiple linear regression comparison.

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Random Forest Preprocessing

Optimizing preprocessing pipeline for Random Forest model.

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Random Forest Preprocessing with Plots

Data preprocessing and visual tracking for Random Forest optimization.

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Random Forest with Cross-Validation

Build and evaluate a random forest model with cross-validation using Python.

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Random Forest with Cross-Validation

Builds and evaluates a Random Forest model with cross-validation and performance metrics.

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Run Simple Linear Regression

Jupyter notebook that runs and explains a simple linear regression model.

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Run Simple Linear Regression

Build and evaluate a basic simple linear regression model in Python.

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SVM 440

Support vector machine analysis and modeling notebook for SVM 440 lab.

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SVM and Neural Network (MLB)

Notebook comparing SVM and NN models on Major League Baseball datasets.

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Salifort Motors Project

Machine learning lab work for Salifort Motors case study.

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Salifort Motors Project Lab

Case study using machine learning to explore performance data at Salifort Motors.

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Set Webhook Script

Python script to set up webhook for automation or GitHub triggers.

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Test Rekognition Model

First implementation of AWS Rekognition on image classification tasks.

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Test Rekognition Model (2)

Second experiment with AWS Rekognition image model.

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Test Rekognition Model 3

Third experimental run of AWS Rekognition with additional images.

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TikTok Analysis (Alt Notebook)

Alternate notebook analyzing TikTok video trends using pandas and matplotlib.

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TikTok Project

Notebook analyzing TikTok data trends using Python and ML techniques.

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Tune and Validate Decision Trees

A deep dive into optimizing decision tree hyperparameters.

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Updated ImageNet Defense (Alt)

Alternative version of the updated adversarial defense implementation using ImageNet.

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Updated ImageNet v2.5 Final

Final version of the adversarial attack and defense pipeline on ImageNet v2.5.

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Use K-Means for Color Compression

Applying K-Means clustering to reduce image color palette for compression.

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Webhook Setup Script

Python script to set and manage webhooks for automation or APIs.

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