Subjects
Foundations of Data Science
The mathematical and statistical underpinnings of the analysis of data and the machine learning algorithms powering the data science and AI revolution.
Probability — Discrete, Random Variables, Stochastic Processes, Measure Theory.
Statistics - Descriptive and Inferential, Parametric and Nonparametric Methods, Bayesian Methods, Maximum Likelihood, Estimator Theory, Statistical Learning Theory, Sampling Methods, Markov Chain Monte Carlo.
Linear Algebra - Vector and Normed Spaces, Matrix Decompositions
Optimization - Linear, Convex, Integer, Mixed Integer, Stochastic
Applied Data Science and Machine Learning
Main tools of the practicing 21st century data scientist — statistical/machine learning algorithms and their implementations and the Python and R data science stacks,
Python — Base, Numpy, Scipy, Pandas, Matplotlib, Seaborn, Bokeh, Statsmodels, Scikit-learn, Hyperopt, Keras, Tensorflow, Pytorch
R - Base, GLM, Tidyverse (Dplyr, GGplot, Tidyr, Readr, Tibble), Tidymodels, Shiny
Machine Learning - Linear Regression, General Linear Models, Supervised, Unsupervised and Ensemble Learning.
Deep Learning - Vanilla Deep Neural Networks, Convolutional, Recurrent, LSTMs.
Preparation and Exploration - Cleaning and Preprocessing, Wrangling, Exploratory Data Analysis, Visualization, Applied Descriptive and Inferential Statistics.
Modeling - Preprocessing, Feature Selection, Feature Engineering, Fitting, Hyperparameter Tuning, Ensembling
Reporting -RStudio, Quarto, Jupyter Notebooks, Jupyter Lab, Markdown, HTML/CSS, LaTeX
Tools - Git, GitHub, Unix cmd line, VS Code, Conda, SQL
Mathematics
The universal language of science, both pure and applied. From rigorous proofs to long derivations to gruesome calculations, help is available in most major areas.
Calculus — Single, Multivariable
Foundations - Mathematical Logic, Set Theory, Category Theory
Analysis - Real, Complex
Algebra - Linear, Abstract
Geometry - Formal, Differential, Algebraic
Topology - Algebraic, Differential
“Think deeply about simple things”
— John Baez, mathematical physicist
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If you need help in any of the subjects above, or are just interested in them, please don’t hesitate to reach out for a free 30 min consultation.