# Posts by Category

## Working with PyTorch’s Dataset and Dataloader classes (part 1)

Recently, I built a simple NLP algorithm for a work project, following the template described in this tutorial. As I looked to increase my model’s complexity...

## PyMC linear regression part 4: predicting actual height

At last, we have come to the end. This is the final post in a series of linear regression posts using PyMC3, from my reading of Statistical Rethinking. Part ...

## PyMC linear regression part 3: predicting average height

This is the next post in a series of linear regression posts using PyMC3. This series has been inspired by my reading of Statistical Rethinking. Part 1 was d...

## PyMC linear regression part 2: understanding the posterior distribution

In a previous post, I wrote about my inital experience using PyMC3. The point was to take a dive deep into some of the package’s objects using a linear regre...

## PyMC linear regression part 1: PyMC objects

I previously wrote about my discovery of Statistical Rethinking. The book’s title could not be more spot-on–it’s helped me look at statistics in a different ...

## Bayes-ball part 3: the credible interval and doing the math

In the last post, we learned about the beta distribution and why it would be a more realistic prior in the context of our problem. We also selected appropria...

## Bayes-ball part 2: a more realistic prior

I meant to post this some time ago, but I have been busy. But with the baseball example I am using, it is only fitting that I post this now, just after this ...

## Bayes-ball part 1: determining a true talent level

In my previous post, we saw how Bayes’ theorem was applied to a relatively simple problem with Bertrand’s box paradox. Here I’ll talk about another applicati...

## Approaching Bertrand’s box paradox, including with Bayes’ theorem

Bayes’ theorem is one of the most useful applications in statistics. But sometimes it is not always easy to recognize when and how to apply it. I was doing s...

## Histograms and recursion in SQL

A few weeks ago, while making a histogram in a SQL query, I discovered that some solutions out there do not include bins with 0 counts. This bugged me so I f...

## F-in statistics!

I recently read this passage in the section on multiple linear regression from the fantastic book Introduction to Statistical Learning:

## Using CASE in the WHERE statement of SQL

Problem statement

## PostgreSQL and Jupyter notebooks

PostgreSQL is one of the most popular variants of SQL. It is common to use PostgreSQL with pgadmin but I am not a big fan of their UI. By contrast, interacti...

## Iterators in Python

One of the things about Python that I haven’t fully appreciated are the use of iterators. I’ll go over some iterators that are a part of base Python and then...

Seems like every statistics class starts off with a coin toss. It’s simple enough for me. Some fancy teachers might start right off the bat and get into the ...

## The probability of making your Friday night party

My wife and I have enjoyed living in the Bay Area where we’ve been able to satisfy our love of outdoor activities while being near a cool city. While we’re f...

## A neuro-educational approach to taking Andrew Ng’s Machine Learning Course

I recently finished Andrew Ng’s fantastic and well-known Machine Learning course through Coursera. As I progress into my data science journey, I felt that ta...

## A ggplot-inspired scatterplot function for Python

I coded for a couple of years in R but switched over to Python almost a year ago. I have to say that I miss R’s ggplot2. Like a lot.

## Working with PyTorch’s Dataset and Dataloader classes (part 1)

Recently, I built a simple NLP algorithm for a work project, following the template described in this tutorial. As I looked to increase my model’s complexity...

## PyMC linear regression part 4: predicting actual height

At last, we have come to the end. This is the final post in a series of linear regression posts using PyMC3, from my reading of Statistical Rethinking. Part ...

## PyMC linear regression part 3: predicting average height

This is the next post in a series of linear regression posts using PyMC3. This series has been inspired by my reading of Statistical Rethinking. Part 1 was d...

## PyMC linear regression part 2: understanding the posterior distribution

In a previous post, I wrote about my inital experience using PyMC3. The point was to take a dive deep into some of the package’s objects using a linear regre...

## PyMC linear regression part 1: PyMC objects

I previously wrote about my discovery of Statistical Rethinking. The book’s title could not be more spot-on–it’s helped me look at statistics in a different ...

## Bayes-ball part 3: the credible interval and doing the math

In the last post, we learned about the beta distribution and why it would be a more realistic prior in the context of our problem. We also selected appropria...

## Bayes-ball part 2: a more realistic prior

I meant to post this some time ago, but I have been busy. But with the baseball example I am using, it is only fitting that I post this now, just after this ...

## Bayes-ball part 1: determining a true talent level

In my previous post, we saw how Bayes’ theorem was applied to a relatively simple problem with Bertrand’s box paradox. Here I’ll talk about another applicati...

## Approaching Bertrand’s box paradox, including with Bayes’ theorem

Bayes’ theorem is one of the most useful applications in statistics. But sometimes it is not always easy to recognize when and how to apply it. I was doing s...

## F-in statistics!

I recently read this passage in the section on multiple linear regression from the fantastic book Introduction to Statistical Learning:

Seems like every statistics class starts off with a coin toss. It’s simple enough for me. Some fancy teachers might start right off the bat and get into the ...

## The probability of making your Friday night party

My wife and I have enjoyed living in the Bay Area where we’ve been able to satisfy our love of outdoor activities while being near a cool city. While we’re f...

## Histograms and recursion in SQL

A few weeks ago, while making a histogram in a SQL query, I discovered that some solutions out there do not include bins with 0 counts. This bugged me so I f...

## Using CASE in the WHERE statement of SQL

Problem statement

## PostgreSQL and Jupyter notebooks

PostgreSQL is one of the most popular variants of SQL. It is common to use PostgreSQL with pgadmin but I am not a big fan of their UI. By contrast, interacti...

## Improving my writing

Introduction I have identified writing well as a skill I will prioritize. This improved skill will benefit both smaller forms I have taken for granted (like...

## Should we mandate instruction practices that are known to improve student learning?

This is a summary of a discussion I led through a discussion group. This group is called the “STEM Education & Diversity Discussion Group” and it is orga...

## Vectorization with np.dot and broadcasting

Vectorization and broadcasting are tricks I have used sparingly and absent-mindedly if at all. However, it is a critical skill for algorithmic code to run ef...

## Iterators in Python

One of the things about Python that I haven’t fully appreciated are the use of iterators. I’ll go over some iterators that are a part of base Python and then...

## Should we mandate instruction practices that are known to improve student learning?

This is a summary of a discussion I led through a discussion group. This group is called the “STEM Education & Diversity Discussion Group” and it is orga...