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isadays/README.md

I'm Isabela, a quantum physicist, data scientist, and computer programmer.

M.Sc. in Quantum Information and M.B.A in Data Science & Analytics at the University of São Paulo. I did an exchange year at the Uppsala University. Technical Studies-Software Development

Python R SQL Qiskit QuTiP Mathematica SymPy PyTorch Pandas NumPy Keras TensorFlow LaTeX C++ HTML5


I build predictive models for both quantum and classical worlds
I am working on an independent project: Quantum neural networks applied to finance and energy.

Summary of Certifications

Advanced Data Science Professional Certificate Quantum Computing Software Certificate Quantum Key Distribution Certificate Financial Risk Management with R Spark, Hadoop, and Snowflake for Data Engineering Spark, Hadoop, and Snowflake for Data Engineering Applied Machine Learning in Python Systems Development Technician

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  1. Unsupervised-ML Unsupervised-ML Public

    Unsupervised Machine Learning techniques (R and Python): CLUSTERING, FACTOR ANALYSIS AND CORRESPONDENCE ANALYSIS

    Jupyter Notebook

  2. Supervised-ML Supervised-ML Public

    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 Sign…

    Jupyter Notebook 1

  3. Supervised-MLII Supervised-MLII Public

    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 para…

    R

  4. DeepLearning DeepLearning Public

    Deep Learning concepts and techniques: Regularization, Epochs, Batch,Hyperparameters, Cross validation, Optimizers

    Jupyter Notebook

  5. BayesianInference BayesianInference Public

    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…

    Jupyter Notebook

  6. ApacheSystemML ApacheSystemML Public

    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 process…

    Jupyter Notebook