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filipeprates's Projects

alc icon alc

Computational Linear Algebra (2023.1) projects

bcggammachallenge2018_finals icon bcggammachallenge2018_finals

BCG Gamma Challenge 2018 Finals in São Paulo. Data from Ideb, predictions, analysis and proposals for brazilian middle school education (only code)

coc361-intelig-ncia-computacional icon coc361-intelig-ncia-computacional

Logistic Regression, Naïve Bayes, Decision Trees, Random Forest, Gradient Boosting, SVMs, Neural Networks compared on Hotel Bookings dataset. Final Report for "COC361 Computational Intelligence" course in UFRJ - June 2021

coe363_hex_colors icon coe363_hex_colors

Simple color picker app using Speech Recognition (Dynamic Time Warping). Project for "COE363 Telecomunications" course in UFRJ

cos360---otimiza-o-n-o-linear-e-n-o-cont-nua icon cos360---otimiza-o-n-o-linear-e-n-o-cont-nua

Optimization analysis of function f(x1,x2) = −ln(x2*(1 − x1)*(1 + x2)*x1). Gradient Descent + Golden-section search + Armijo + Newton's method + quasi-Newton's method. Final Report of "COS360 Optimization - Linear and non-linear, Continuous and non-continuous"

cos470-distributed-systems--trab2--thread-sync icon cos470-distributed-systems--trab2--thread-sync

[C++] Multi-thread synchonizarion. Locks and Mutex. Producer-Consumer threads with protected buffers. Paralellizing a large sum (vector of size up to 10^9). [Python] Data Visualization of results. Report for "COC470 Distributed Systems".

cps765-complex_networks-projeto_final-similaridade_entre_alunos icon cps765-complex_networks-projeto_final-similaridade_entre_alunos

This article uses a dataset of answers to questions to generate student similarity networks. Two similarity functions to determine the weights between each pair of students are used, one that assumes a power-law distribution of answers response times, and one that does not. The resulting networks are then clustered using different communi

desafio-data-eng icon desafio-data-eng

Desafio de Engenharia de Dados para o Escritório de Dados da Prefeitura do Rio de Janeiro (Data Engineering Challenge for Rio de Janeiro City Government)

eel816_human-engine_chess icon eel816_human-engine_chess

A variant on top of "Hand & Brain" chess, using speech interface. A player vocalizes the type of a piece [Pawn,King,Queen,Bishop,Knight,Rook], the Engine (StockFish 11) will play on the board what they regard as the best move with such piece type. Then it's the other player's turn. Game logic on Assets/Python. https://docs.google.com/presentation/d/1YOBRfllSFd9a2kmSXaNBtiMBxVp-5ADj-kDxY774jM4/edit?usp=sharing

emd-desafio-civitas icon emd-desafio-civitas

Desafio CIVITAS (Filipe Santos Pacheco Prates - [email protected]) - Análise exploratória dos dados, identificar inconsistências, além de identificar placas de veículos que foram possivelmente clonadas, usando as informações disponíveis. Slides:

happyset-ic icon happyset-ic

For an undirected graph G = (V, E) and a subset S ⊆ V of vertices, a vertex v is happy if v and all its neighbors are in S; otherwise unhappy. Given an undirected graph G = (V, E) and an integer k, the goal of MaxHS is to find a subset S ⊆V of k vertices such that the number of happy vertices is maximized.

intuitive-management-interface-for-graph-database icon intuitive-management-interface-for-graph-database

This repo describes an intuitive interface for management of graph data, allowing for easy navigation and arbitrary manipulation of the nodes and edges. As an example, it describes an implementation using a Neo4j database that is managed through a GraphQL API and a Vue.js web interface.

intuitivemanagementinterfaceforneo4jgraphdatabase icon intuitivemanagementinterfaceforneo4jgraphdatabase

This article describes an intuitive interface for management of graph data, allowing for easy navigation and arbitrary manipulation of the nodes and edges. As an example, it describes an implementation using a Neo4j database that is managed through a GraphQL API and a Vue.js web interface.

laff-on-pfhp icon laff-on-pfhp

Repository for "LAFF-On Programming for High Performance"

modelosestprob icon modelosestprob

Analysing medical data to predict Max VO2. CDF, PMF, Exponential, Gaussian, Weibull, Log-Normal distributions, Linear Regression. Final Report for "COC361 Statistics and Probabilistic Models" course in UFRJ.

trabalhografos icon trabalhografos

Graph Library - Store and build graphs as adjacency matrix or adjacency list, run BFS, DFS starting at arbitrary vertex, find the connected components and analyze the vertex's degree distribution. Final Report for "COS242 Graph Theory" course in UFRJ

zepequeno icon zepequeno

Code for Sumo Robot "Zé Pequeno" of MinervaBots - Robotics team @UFRJ

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