This repository contains personal projects I did in my free time and during my CS master's degree.
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The goal of this competition was to predict which clients are more likely to default on their loans where evaluation favored solutions that are stable over time
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The goal of this competition was to use various factors to predict obesity risk in individuals, which is related to cardiovascular disease
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This competition involved creating an energy prediction model of prosumers to reduce energy imbalance costs.
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The challenge revolved around forecasting store sales on data from Corporación Favorita, a large Ecuadorian-based grocery retailer.
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The challenge revolved around constructing a machine learning model adept at distinguishing genuine disaster-related tweets from others.
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Kaggle Digit Recognizer Competition (10/2023)
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The challenge entailed the accurate identification of digits from a dataset comprising tens of thousands of handwritten images.
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This competition involved forecasting sales with synthetically generated time series datasets.
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Kaggle ConnectX RL Competition (07/2023)
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The ConnectX competition involves training an AI agent to play Connect4, and contestants are required to submit their agent in a Python file for evaluation on the leaderboard.
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This folder contains notebooks I created for exploratory data analysis and visualization of interesting datasets obtained from Kaggle.
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Kaggle Titanic ML Competition (06/2023)
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Titanic competition is about developing a machine learning model that makes binary classifications from tabular data of Titanic's passengers.
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The project involved training an AI agent who plays the Flappy Bird game using deep reinforcement learning.
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Building an Interactive dashboard with Vega-Lite to visualize nuclear explosions worldwide (04/2023)
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I created an interactive dashboard using Vega-Lite to visualize nuclear explosions worldwide.
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The project involved building a deep convolutional neural network model to recognize monkey species from disparate images.
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The project involved creating a gradient-boosting regressor for continuous prediction problems by inheriting from appropriate scikit-learn base classes.
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Data mining and text analysis for gaining insight into the common traits employers currently look for in data analytics roles.
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I implemented a Multi-Layer Neural Network from Scratch with Python without using any ML library.
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This is a combination of two projects for using big data management tools, Hadoop and Spark.
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I built Time-Related Feature Engineering Pipelines and developed a machine learning model with Python to predict traffic volumes.
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This folder contains studies for practicing Data Warehousing and association rule mining.
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I implemented a small database management system in Bash.
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My CodeWars Solutions (on-going)
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This folder contains my solutions for coding challenges.
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