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
Fluent in Python and R and their data science stacks. Well-versed in the major tools of the practicing 21st century data scientist.
Python — Base, Numpy, Scipy, Pandas, Matplotlib, Seaborn, Bokeh, Statsmodels, Scikit-learn, Hyperopt, Keras, Tensorflow, Pytorch
R - Base, GLM, Tidyverse (Dplyr, GGplot, Tidyr, Readr, Tibble), Shiny, Simstudy
Machine Learning - Linear Regression, General Linear Models (Logistic, Poisson,…), Supervised (K-Nearest Neighbors, Support Vector Machines, Kernel Methods,….) Unsupervised (PCA, Clustering) Ensemble Learning (Random Forests, Gradient Boosted Machines, Stacking, Blending)
Deep Learning - Vanilla Deep Neural Networks, Convolutional, Recurrent, LSTM
Ingestion and Storage - Streaming, Scraping, SQL, NoSQL
Preparation and Exploration - Cleaning and Preprocessing, Applied Descriptive and Inferential Statistics, Exploratory Data Analysis, Visualization
Modeling - Preprocessing, Feature Selection, Feature Engineering, Fitting, Hyperparameter Tuning, Ensembling
Reporting - RStudio, Jupyter Notebooks, Jupyter Lab, Markdown, HTML/CSS, LaTeX
Mathematics
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
Book a Meeting
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.