- Fast and Intuitive Statistical Modeling with Pomegranate - Dec 21, 2020.
Pomegranate is a delicious fruit. It can also be a super useful Python library for statistical analysis. We will show how in this article.
Distribution, Markov Chains, Probability, Python, Statistical Modeling
- Practical Markov Chain Monte Carlo - Jun 26, 2020.
This is a slightly more intricate example of MCMC, compared to many with a fairly simple model, a single predictor (maybe two), and not much else, which highlights a couple of issues and tricks worth noting for a handwritten implementation.
Bayesian, Markov Chains, Monte Carlo, R
- A Comprehensive Guide to Natural Language Generation - Jan 7, 2020.
Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.
LSTM, Markov Chains, Narrative Science, Natural Language Generation, Natural Language Processing, Recurrent Neural Networks, Sciforce, Transformer
- Markov Chains: How to Train Text Generation to Write Like George R. R. Martin - Nov 29, 2019.
Read this article on training Markov chains to generate George R. R. Martin style text.
Generative Models, Markov Chains, NLP, Text Analytics
- Explaining Reinforcement Learning: Active vs Passive - Jun 26, 2018.
We examine the required elements to solve an RL problem, compare passive and active reinforcement learning, and review common active and passive RL techniques.
Active Learning, Markov Chains, Reinforcement Learning
- 5 Things You Need to Know about Reinforcement Learning - Mar 28, 2018.
With the popularity of Reinforcement Learning continuing to grow, we take a look at five things you need to know about RL.
Machine Learning, Markov Chains, Reinforcement Learning, Richard Sutton
Introduction to Markov Chains - Mar 15, 2018.
What are Markov chains, when to use them, and how they work
Markov Chains
- What Statistics Topics are Needed for Excelling at Data Science? - Aug 2, 2016.
Here is a list of skills and statistical concepts suggested for excelling at data science, roughly in order of increasing complexity.
Bayesian, Distribution, Machine Learning, Markov Chains, Probability, Regression, Statistics
