Brian Céspedes

With a background in Physics and as a Data Scientist I provide support in these areas:

• Data Science: Machine Learning in R and Python: Simple, Multiple and Polynomial Regression, SVR, Logistic Regression, K-NN, SVMs, Naive Bayes, Decision Tree and Random Forest Regression and Classification, K-Means, Hierarchical Clustering, NLP, Q-Learning and Transfer Learning, Deep Learning with ANNs and CNNs, Deep Belief Networks and Dimensionality Reduction. Big Data Analysis with Apache Spark.

• CRAN, NeuroLab, PyBrain, Tesseract, Caffe, Theano, Keras and TensorFlow.

• Computational Physics: Finite Difference Method, Monte Carlo methods, Ising
Model, Finite Size Scaling, Lennard-Jones fluids, ODEs and PDEs Applications, Fourier Transforms, Verlet Algorithms, Phase Transitions and Brownian Dynamics.

• Phyton, R, Scala, C++, Fortran, Matlab, Processing, SQL and MySQL.

• Finite Element Analysis: Abaqus, CST Studio, Solidworks, Comsol
Multiphysics and ANSYS Fluent.

Best regards!