Joaquin Molto

Joaquin Molto

@FIUPanther-JMolto98

Web 🌐 + AI/ML 🦾

Miami, FL
15
Followers
35
Following
11
Public Repos
0
Private Repos

Language Breakdown

Lines of code distribution across 11 owned repositories

35.8M Total LOC
HTML
19,468,234 lines
54.5%
N/A
Jupyter Notebook
15,649,219 lines
43.8%
N/A
Python
243,960 lines
0.7%
N/A
JavaScript
204,934 lines
0.6%
N/A
MATLAB
127,560 lines
0.4%
N/A
Other
57,841 lines
0.2%
N/A
T

T-Shaped Developer

T-shaped

Deep in HTML with broad versatility

HTML
Jupyter Notebook
Python
JavaScript
MATLAB

Collaboration Network

Global Impact visualization

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Joaquin Molto
0 active collaborators

Repos

16

PRs

0

Growth

+18%

Top Collaborators

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Coding Streak

Contribution activity over the past year

20 days
466
Contributions
1
Commits
0
Pull Requests
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Top Repositories

Citizens-Dashboard

Web application that allows citizens from specific municipalities, counties, cities, and states to discuss about recent legislations, community initiatives, and more by creating posts and linking sources to neutralize bias. Powered by AI/ML to generate summaries for the legislations uploaded into the knowledgebase and interact with the documents

1 0
TypeScript
NeuroGlimpse

React-based project allows users to interact with several Open-Source Transformers from HuggingFace via the SDK. The dashboard-like GUI consists of several widgets that allow users to see the probability distribution of next token after softmax() in decoders, difference in between masked and full self-attention, and embedding visualizations

1 0
HTML
EEL5813_PRJ03_MLP_Backpropagation_Momentum_EKG-MCI

Repository contains my MATLAB files for the hand-coded Myocardial-Infarction detection model trained on EKG data whose features were carefully engineered for the EEL5813 - Neural Networks: Algorithms and Applications course, PROJECT03

0 0
MATLAB
EEL5813_PRJ02_MLP_Backpropagation_MNIST

Repository contains my MATLAB files for the hand-coded MNIST (w/ SGD optimizer) classification model trained for the EEL5813 - Neural Networks: Algorithms and Applications course, PROJECT02

0 0
MATLAB
EEL5813_PRJ01_Perceptron_ADALINE_Handwritten_Vowel_Detector

Repository contains my MATLAB files for the hand-coded perceptron vowel-detection model (w/ ADALINE) architecture for the EEL5813 - Neural Networks: Algorithms and Applications course, PROJECT01

0 0
MATLAB
EEL6812_PRJ03-Recurrent-Neural-Network-LSTM

Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Recurrent Neural Network (RNN) regressor model that predicts energy demand in t-horizon, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ03

0 0
Jupyter Notebook
EEL6812_PRJ02-Convolutional-Neural-Network

Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Convolutional Neural Network (CNN) that classifies Dogs, Cats, and Pandas, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ02

0 0
Jupyter Notebook
EEL6812_PRJ01-Regressor-Classificator

Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Multilayer Perceptron (MLP) capable of predicting wine scores and classifying quality, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ01

0 0
Jupyter Notebook
CalcWiz

Multimodal, intelligent LLM and RAG-powered math tutor capable of combining the power of NLP with CAS to produce answers that are mathematically-sound, hallucination-free, and easy to digest with step-by-step solutions delivered using natural language. Support LaTeX front-end rendering with libraries such as MathJax

0 0
JavaScript
Maze_Maker_Solver

Simple Python project that uses standard libraries in conjunction with PyGame for the GUI. Allows the user to create a maze using their mouse, define starting position [S_i,S_j], goal position [G_i,G_j], and run different pathfinding algorithm visualizations from informed (Greedy, A*) to uninformed (DFS,BFS) and choose between L1 and L2 heuristics

0 0
Python

Open Source Impact

Contributions to external projects

0 merged PRs
Contributed to 1 repositories