Amario Fausta's repositories
Clustering-Model-for-Product-Ownership-Determination
Customer Clustering : Identify product ownership patterns based on customer demographics using K-Means & K-Medoids clustering.
FinanKu-Credit-Risk-Prediction
Building a financial customer default risk prediction model using Machine Learning with financial data.
Fraud-Detection
"Retail transaction fraud detection project with machine learning models on the Data Mining Cup 2019 dataset."
Cohort-Analysis-in-Python
Perform cohort analysis on retail data to understand customer retention over time using Python. Visualize results in a heatmap.
Retention-Analysis
This GitHub repo analyzes online retail data, cleansing and conducting cohort analysis. Explore insights through data visualizations
Churn-Prediction
Predict customer churn using ML. Analyze data, build models, and evaluate performance. Make informed business decisions.
Retail-Rationalization-Business-Clustering
This code is a case study on optimizing retail stores through location analysis, clustering, and store rationalization.
IMDB_Text_Sentiment
Perform sentiment analysis on IMDB movie reviews using logistic regression, predicting positive or negative sentiments. Preprocess data, create BoW and TF-IDF features, build a logistic regression model, and evaluate its performance. Visualize common words in positive and negative reviews.
Technical-stocks-Analysis
"Analyze and visualize stock data with Python, leveraging Pandas, Matplotlib, and Seaborn for insights."
Data-science-region-dataset
"Data analysis of regional survey dataset, exploring demographics, interests, and visualizing insights."
Blaze
"Innovative, responsive, and efficient - Welcome to our GitHub repository! Here, we run passionately driven projects, focusing on creative solutions to technical challenges. Explore the code, documentation, and other valuable resources for deep insights into what we're working on. Let's collaborate and create together!"
Phi-estimator-using-Monte-Carlo
## Monte Carlo Pi Estimation using Pygame This repository provides a Python script that demonstrates the estimation of the mathematical constant Ο (pi) using the Monte Carlo simulation method. The script uses the Pygame library to visualize the simulation process by plotting random points within a quarter circle and determining the ratio of points
Preceptron-without-sklearn
This repository contains a custom implementation of the Perceptron learning algorithm for binary classification. The code demonstrates the step-by-step process of training, iterative refinement, testing, and accuracy calculation using a simple perceptron model. Gain a deeper understanding of binary classification fundamentals without relying to lb
Tensor-RT
Welcome to the "Optimization and Deployment of TensorFlow Models with TensorRT" workshop! In this hands-on session, you'll gain expertise in enhancing inference performance using TensorFlow's integration for TensorRT (TF-TRT). Discover the art of optimizing deep learning models at various precisions, understand the mechanics of TF-TRT π€π
Left-Ventricel-Segmentation
This repository offers an immersive introduction to image segmentation using the TensorFlow machine learning framework. Image segmentation is vital in various image analysis applications, going beyond object detection to segment images into distinct spatial regions of interest. Explore hands-on training and evaluating image segmentation networks
Iris-Flower-Classification-Perceptron
Welcome to this repository! Here, you'll find source code and tutorials for performing Iris flower classification using the Perceptron classification model. This repository guides you through the fundamental steps of building, training, and evaluating a machine learning model to classify Iris flowers based on their morphological features.
Patient-Mortality-Prediction-Using-LSTM
## Patient Mortality Prediction Using LSTM π₯π Welcome to the Patient Mortality Prediction Using LSTM repository! This project combines medical insights with advanced deep learning techniques to forecast patient mortality based on pediatric intensive care unit (PICU) data.
Rain-Simulation-using-Piezoelectric-Material-Monte-Carlo
This GitHub repository features a Python program that simulates raindrop impacts on a piezoelectric material surface using the Monte Carlo method. π§οΈπ‘ The program employs the 'pygame' library for interactive visualization and 'matplotlib' for data plotting, offering an engaging depiction of raindrop impacts and energy generation on the material
Fruit-ripeness-CNN
This repository contains a deep learning project focused on classifying fresh and rotten fruits using transfer learning, data augmentation, and fine-tuning techniques. The project utilizes a VGG16 base model pretrained on ImageNet and aims to achieve a validation accuracy of 92% or higher on a dataset comprising various fruit categories.
Headline-Generator-Natural-Language-Processing
In this project, we'll delve into sequence data, shifting from standalone data like images to dependent sequential data like text sentences. The focus will be on utilizing recurrent neural networks (RNNs) to predict subsequent words in a sentence. Through a simple model, we'll prepare and train it to perform this word prediction task. This project
Pretrained-model-CNN
Explore the realm of transfer learning in this workshop, crafting an automated doggy door that distinguishes a specific canine from others using pre-trained models and a small dataset. Through guided steps, delve into model training, data augmentation, and fine-tuning, gaining hands-on experience in the art of transferring knowledge from existing m
American-Sign-Language-Augmentation-and-CNN
This repository contains code and resources for building a Convolutional Neural Network (CNN) that can recognize American Sign Language (ASL) images. The model is capable of classifying letters in ASL using high accuracy. The process involves data preprocessing, creating a CNN model, training, evaluation, and utilizing the trained model to recogniz
American-Sign-Language-CNN
"Repository containing code and resources for ASL (American Sign Language) image classification using Convolutional Neural Networks (CNNs). Learn data preprocessing, CNN architecture, training, and evaluation for accurate ASL letter recognition."
American-Sign-Language
Explore image classification using American Sign Language (ASL) dataset. Build, train, and evaluate a neural network model to recognize ASL letters. Learn data preprocessing, model creation, and understand overfitting. Part of a comprehensive learning journey into deep learning techniques.
MNIST_Tensorflow
MNIST Digit Recognition with TensorFlow Implementation of digit recognition using TensorFlow and the MNIST dataset. Train a neural network model to classify handwritten digits (0-9) with high accuracy.
Machine-learning-arduino
Machine Learning Prediction on Arduino with MicroML Explore the world of embedded machine learning with MicroML. Train and deploy lightweight models on Arduino for real-time predictions. This repository showcases various classifiers and models compatible with MicroML, enabling predictive capabilities on resource-constrained devices.
Snake-and-ladder-monte-carlo
Monte Carlo Random Snake Game Experience a novel twist on the classic Snake Game using Monte Carlo randomness. This repository features an engaging Snake Game where the movements are guided by Monte Carlo simulation-based random choices, resulting in an unpredictable and entertaining gaming experience.
Freely-Falling-Object-Calculation-Using-YOLOv3
YOLOv3 for Freely Falling Object Calculation Explore the world of physics with YOLOv3 object detection. This repository showcases the utilization of YOLOv3 for tracking and calculating the motion of freely falling objects. Witness real-time object detection and learn about gravitational physics in action.
Advanced-Lane-Detection
Advanced Lane Detection with Sliding Windows Dive into computer vision with advanced lane detection using the sliding windows technique. This repository demonstrates how to identify and track lanes on road images or videos. Explore the intricacies of image processing and lane tracking algorithms to enhance your understanding of self-driving car te