Isabela Dias's repositories
IDA-Historical-Data
Using IDA historical data to predict the country which has a probability greater than 0.1 of being in debt with IDA.
Non-MarkovianDynamics
Qutip Monte Carlo to solve the dynamics of time-local non-Markovian master equations
ApacheSystemML
The purpose of this repository is to process data , prepare it, and build models to predict certain activities using ML techniques. The entire process leverages PySpark for distributed data processing . The codes were developed according to Advanced Machine Learning and Signal Processing and Applied Ai with deeplearning courses from IBM.
BayesianInference
The model predicts the treatment success rate for new TB cases with high accuracy and robustness. Two different approaches: PCA and Bayesian Inference. The Bayesian regression analysis reveals that c_new_sp_tsr and new_sp_fail are significant predictors of the treatment success rate, while other predictors show less certainty in their effects.
BB84-Protocol
Simulation of the BB84 Protocol
cadastro-de-curriculos
Sistema Web para cadastros de currículos online. Criado utilizando PHP em arquitetura MVC.
Co2emissions
Cleaning data using decision tree and k-nn techniques
CreditCardFraud
Credit Card Fraud detection with neural networks(anomaly detection) and machine learning techniques (random forest classifier)
DeepLearning
Deep Learning concepts and techniques: Regularization, Epochs, Batch,Hyperparameters, Cross validation, Optimizers
Supervised-ML
OLS. R and Python. In this project, we study fundamental concepts of Supervised ML models, such as Regression Analysis: Coefficient of Model Adjustment (R²), Parameters Estimation ,Statistical Significance of the Model (F test, T test) ,Multiple Regression , Qualitative Explanatory Variables (X) , heteroscedasticity and etc.
Supervised-MLII
Scripts in R.Logistic Models. In this project, we explore theoretical foundations, Model specification and canonical connection functions, Binary and multinomial logistic models, Estimation of parameters by maximum likelihood, Cutoff, sensitivity, specificity, ROC curve and GINI index
SystemSecurity
Improving system security using neural networks
Unsupervised-ML
Unsupervised Machine Learning techniques (R and Python): CLUSTERING, FACTOR ANALYSIS AND CORRESPONDENCE ANALYSIS
Energy
Cleaning data using data analysis and exploratory analysis techniques
ErrorCorrection
In this project, I explore the expedient and stringent protocols, both quantum error correction protocols designed to protect quantum data from errors.
Financial-Analysis
Visualizing and Munging Stock Data
HPC-Project
Course: Introduction to scientific computation - Final project HPC- Creation of container and parallel job using OpenMP and MPI
LateXPresentation
Lecture presented in the course Inglês em Contexto Acadêmico
livre
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MachineLearning-Assignment
Assignment 3 - Course Applied Machine Learning
ProjectDataVisualization
Project presented to the course Applied Plotting, Charting & Data Representation in Python, University of Michigan
SQL_Script
Assignment 3 - Course Database Management Essentials, University of Colorado System
Time-symmetricFormulation
In this code, I reproduce the results from Ref. Entropy 2021, 23(2), 179;
Valuation-Strategy
M&A, Private Equity and Venture Capital
VisualDataAnalysis
Python scripts using the Visualization Toolkit (VTK) and Topology ToolKit (TTK) libraries. Tasks: visualize and explore topological features of a 3D volume and 2D scalar field datasets. 1. Probability density for the 3d electron position in a hydrogen atom and 2. 2D scalar field.