Engineer, Entrepreneur, Innovator
Welcome to my blog where I share the latest in my work and interests.
If you like what you see here, please visit the main page of my website to learn more about me!
Hi all! I'm a huge bibliophile and quite avid about education. In the context of my work in data science as a machine learning engineer, I've had to learn a lot of material extremely quickly. Every new model build brings with it a new learning curve. Below I've listed by favorite online tutorials, books, and research papers for learning about various interesting topics. You can also find the recommendations below, and more, in this google sheet: Paper Trail Google Sheet
Here are a few of my favorite text books for learning about topics in data science.
Topic | Book Title | Main Author | Reading Level | Source |
---|---|---|---|---|
Causal Inference | Causality | Pearl | Expert | LINK |
Causal Inference | Counterfactuals and Causal Inference | Winship | Expert | LINK |
Causal Inference | Causal Inference: What If 2 | Robins | Practitioner | LINK |
Cyber Security | Network Security and Cryptology | Musa | Introductory | LINK |
Cyber Security | Counter Hack Reloaded | Skoudis | Introductory | LINK |
Evolutionary Algorithms | Essentials of Metaheuristics | Luke | Practitioner | LINK |
Filtering | Bayesian Filtering and Smoothing | Sarkka | Practitioner | LINK |
Graphs | Networks, Crowds, and Markets | Kleinberg | Expert | LINK |
Graphs | Network Science | Barabasi | Introductory | LINK |
Graphs | Networks | Newman | Practitioner | LINK |
Machine Learning | Advanced Data Analysis from an Elementary Point of View | Shalizi | Expert | LINK |
Machine Learning | Generalized Linear Models | Nelder | Introductory | LINK |
Machine Learning | Foundations of Data Science | Kannan | Introductory | LINK |
Machine Learning | Pattern Recognition and Machine Learning | Bishop | Practitioner | LINK |
Machine Learning | Doing Analysis using Regression and Multilevel/Hieratchical Models | Gelman | Practitioner | LINK |
Machine Learning | Pattern Classification | Duda | Practitioner | LINK |
Markov Chain Monte Carlo | Handbook of Markov Chain Monte Carlo | Gelman | Introductory | LINK |
Markov Chain Monte Carlo | Monte Carlo Statistical Methods | Casella | Introductory | LINK |
Markov Chain Monte Carlo | Markov Chain Monte Carlo in Practice | Gilks | Practitioner | LINK |
Markov Chain Monte Carlo | Monte Carlo Strategies in Scientific Computing | Liu | Practitioner | LINK |
Natural Language Processing | Neural Network Methods for Natural Language Processing | Goldberg | Practitioner | LINK |
Neural Network | Neural Networks and Deep Learning | Nielsen | Introductory | LINK |
Neural Network | Deep Learning | Goodfellow | Practitioner | LINK |
Optimization | Algorithms for Optimizations | Kochenderfer | Introductory | LINK |
Probabalistic Graphical Models | An Introduction to Probabilistic Graphical Models | Jordan | Practitioner | LINK |
Probabalistic Graphical Models | Machine Learning: A Probabilistic Perspective | Murphy | Practitioner | LINK |
Probabalistic Graphical Models | Probabilistic Graphical Models | Koller | Practitioner | LINK |
Quality Control | Introduction to Statistical Quality Control | Montgomery | Introductory | LINK |
Reinforcement Learning | Deep Reinforcment Learning Hands-On | Lapan | Practitioner | LINK |
Reinforcement Learning | Reinforcment Learning An Introduction | Sutton | Practitioner | LINK |
Statistics | Statistical Analysis | Kachigan | Introductory | LINK |
Statistics | A Modern Introduction to Probability and Statistics | Dekking | Introductory | LINK |
Statistics | Statistical Inference | Casella | Introductory | LINK |
Statistics | Handbook of Biological Statistics | McDonald | Introductory | LINK |
Statistics | Mostly Harmless Economics | Pischke | Introductory | LINK |
Statistics | Experimental Design | Cox | Introductory | LINK |
Statistics | Sampling Techniques | Cochran | Introductory | LINK |
Statistics | Field Experiments | Gerber | Introductory | LINK |
Statistics | Monte Carlo Strategies in Scientific Computing | Liu | Practitioner | LINK |
Statistics | Design of Observational Studies | Rosenbaum | Practitioner | LINK |
Statistics | Sampling: Design and Analysis | Lohr | Practitioner | LINK |
Statistics | Graphical Models, Exponential Families, and Variational Inference | Jordan | Practitioner | LINK |
Statistics | Handbook of Statistical Methods | NIST | Practitioner | LINK |
Statistics (Bayesian) | Gaussian Processes for Machine Learning | Rasmussen | Expert | LINK |
Statistics (Bayesian) | Statistical Descision Theory | Berger | Expert | LINK |
Statistics (Bayesian) | Statistics for Spatio-Temporal Data | Cressie | Expert | LINK |
Statistics (Bayesian) | Geostatistics: Modeling Spatial Uncertainty | Chiles | Expert | LINK |
Statistics (Bayesian) | Probabalistic Reasoning in Intelligent Systems | Pearl | Expert | LINK |
Statistics (Bayesian) | Probabilistic Programming and Bayesian Methods for Hackers | Davidson-Pilon | Introductory | LINK |
Statistics (Bayesian) | Statistical Rethinking | McElreath | Introductory | LINK |
Statistics (Bayesian) | A Student's Guide to Bayesian Statistics | Lambert | Introductory | LINK |
Statistics (Bayesian) | Think Bayes | Downey | Introductory | LINK |
Statistics (Bayesian) | Theory of Probability | Jeffreys | Introductory | LINK |
Statistics (Bayesian) | The Foundations of Statistics | Savage | Introductory | LINK |
Statistics (Bayesian) | Doing Bayesian Data Analysis 1 | Kruschke | Introductory | LINK |
Statistics (Bayesian) | Probability Theory | Jaynes | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Data Analysis | Gelman | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Probability Theory: Applications in the Physical Sciences | Linden | Practitioner | LINK |
Statistics (Bayesian) | Information Theory, Inference, and Learning Algorithms | MacKay | Practitioner | LINK |
Statistics (Bayesian) | The Bayesian Choice | Roberts | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Artificial Intelligence | Korb | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Nonparametrics | Ghosh | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Nonparametrics | Muller | Practitioner | LINK |
Statistics (Bayesian) | Modeling and Reasoning with Bayesian Networks | Darwiche | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Learning for Neural Networks | Radford | Practitioner | LINK |
Statistics (Bayesian) | Bayesian Forcasting and Dynamic Models | Harrison | Practitioner | LINK |
Time Series | Introduction to Time Series | Brockwell | Introductory | LINK |
Time Series | Elements of Forecasting | Diebold | Introductory | LINK |
Time Series | Time Series Analysis | Hamilton | Introductory | LINK |
Time Series | Introduction to Time Series Analysis and Forecasting | Montgomery | Introductory | LINK |
Time Series | Nonlinear Time Series | Fan | Practitioner | LINK |
Time Series | Timeseries | Hamilton | Practitioner | LINK |
1. Python version of examples:
Doing Bayesian Data Analysis
2. Python version of examples:
Causal Inference: What If
If text books aren't your thing, here are a few awesome online courses.
Topic | Course Title |
---|---|
Reinforcement Learning | Berkeley Deep Reinforcement Learning |
Reinforcement Learning | University College London Reinforcement Learning |
Signal Processing | Filtering in Python |
Machine Learning | Lazy Programmer Inc. |
Statistics | Statistics and Probability |
Statistics | MIT Introduction to Probability and Statistics |
Linear Algebra | MIT Linear Algebra Sprint 2010 |
Machine Learning | Stanford CS229 |
Statistics | Seeing Theory |
Statistics | StatLec |
Data Visualization | Fundamentals of Data Visualization |
A big part of my professional development is education, both teaching and learning. I'm a firm believer that we should constantly strive to further our education throughout our lives. I've always enjoyed taking classes and reading books on a diverse range of subjects from glass blowing to the study of the Greek classics. Here I've listed a few blogs I've found to be extremely influencial on my education in datascience. Make sure to check out my own personal blog too!
Radford Neal's Blog
Eric Jang's Blog
While My MCMC Gently Samples
Stratechery
The Morning Paper
Lillian Weng
Darren Wilkinson's Blog
District Data Labs
Distill
Hacker News
Jason Wittenbach's Github
Mack Sweeney's Github
Josh Touyz' Blog
Keegan Hines' Blog
covert.io
I also love listening to podcasts on my commute to work or on long hikes. Here are a few of my favorite technical podcasts.
Security Now
Command Line Heroes (Redhat)
Stratechery
Lex Friedman AI Podcast