Machine Learning and Side Projects
This is a partial list of my Machine Learning and Data Science projects completed in my free time or for academic courses. Main findings and challenges are highlighted and reported using R Notebooks or IPython Notebooks. My professional projects are not included.
Tactile-Informed 3D Gaussian Splatting
Reconstructing challenges surfaces with vision and tactile sensing within a 3D Gaussian Splatting framework.
- PYTHON
- PYTORCH
TouchSDF
Implementation of the TouchSDF paper on 3D shape reconstruction using vision-based tactile sensing.
- PYTHON
- PYTORCH
DeepSDF
Implementation of the paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation with shape completion functionality.
- PYTHON
- PYTORCH
3D Shape Reconstruction using Vision Based Tactile Perception
Reconstructing 3D object shapes using Graph Neural Networks and robotics tactile sensing.
- PYTHON
- PYTORCH3D
- PYBULLET
Monte Carlo Path Tracer
Implementation of different standard Monte Carlo approaches in path tracing, and comparison with Next Event Estimation
- C++
Q-Learning for Monte Carlo importance sampling
Reinforcement Learning-based approaches applied to the light transport equation for importance sampling
- C++
Deep Reinforcement Learning for Games
Deep Q-Learning agent to play the game Snake. Optimized it using Bayesian Optimization
- PYTHON
- PYTORCH
- TENSORFLOW
- DEEP REINFORCEMENT LEARNING
- BAYESIAN OPTIMIZATION
Artificial Intelligence meets Art: Neural Transfer Style
Deep Learning technique to transfer the style of a painting to a chosen image
- PYTHON
- TENSORFLOW
- DEEP LEARNING
- KERAS
Monte Carlo Tree Search: Tic Tac Toe
MCTS strategy to play the game Tic tac Toe
- PYTHON
- MCTS
Flight Delay Prediction
Modeling and predicting the delay of 7 million US domestic flights using Big Data Tools.
- SPARK
- SCALA
- R
Highway patrol
Java application using Flink, implementing functionalities of Speed Radar, Average Speed Control and Accident Reporter on data streams.
- JAVA
- FLINK
- DATA STREAM
TPC-C Benchmark
Java program using HBase to create, load tables, and implementing four different queries to simulate the activity of any company that manages, sells, and distributes products or services.
- JAVA
- HBASE
- HADOOP
Raw data processing for diseases prediction
Processing raw data to feed a machine learning model using IBM SPSS Modeler.
- PYTHON
- RAW DATA
