All You Can Pay: How Companies Use Our Data to Empty Our Wallets explains how Big Data companies are not just emptying our wallets but changing our world. Authors Anna Bernasek and D.T. Mongan illustrate through easy to understand stories and thoughtful analysis how the use of data is changing the economy. From price discrimination to dynamic pricing and customization, Big Data is dismantling the traditional free market economy.

But what is the free market and why does it matter? The free market is a market where buyers and sellers “willingly exchange goods and services for mutual benefit.” (p.172) This…

Boot camps or career accelerator programs are short-term education programs designed to help you learn new skills and find a job. I recommend boot camps for experienced folks switching into tech from different fields. The real value in boot camps is the career placement assistance that they provide. But boot camps aren’t for everyone so I recommend doing lots of research before considering attending one.

I will share some tips about finding a boot camp in the USA, my story about how I chose to attend Codeup in San Antonio, TX, and how I got funding to attend. …

Article by Erna Fiorentini: “Inducing visibilities: An attempt at Santiago Ramón y Cajal’s aesthetic epistemology” / Studies in History and Philosophy of Biological and Biomedical Sciences 42 (2011) 391–394

Erna Fiorentini’s study on the scientist Santiago Ramón y Cajal, the father of neuroscience, introduces the idea of “aesthetic epistemology” to describe the method by which Cajal studied histology. Histology is the study of the anatomy of cells and tissues of plants and animals using microscopy. By its very nature, histology is a field of study where we cannot directly observe the thing studied.

“Aesthetic epistemology” as theorized by Fiorentini describes…

This article is a simple summary of my notes on Linear Regression; explain it like I’m 5 version.

Linear Regression is a foundational machine learning algorithm, which is supervised — meaning we know what the data represents. It is used to model the relationship between two or more things, i.e., one or more features and an outcome / result.

Some of the questions we could pursue using a linear regression analysis include: What is the relationship between this variable and that variable? Do these set of variables have a significant correlation with a particular outcome?

The ultimate goal of linear…

My programming journey, from knowing nothing to learning some programming skills to getting a job in tech, has been transformational and challenging. And definitely not linear! This skillset is rewarding, profitable and attainable for most people. I am hopeful that my experiences and perspective on programming will inspire other people with little to no programming experience to learn how to code!

Watch my video about My First Line of Code on my Youtube Channel. Or else read below.

How did I begin programming?

I started coding in my twenties. I quit more than once because it was hard and I…

In this article, I share the top 3 things that I learned about working in the tech industry as a boot camp graduate. My first year and a half in industry was rough. After toiling and hustling to break into a new tech career, the work place became a wild jungle for me. I struggled with anxiety and health issues, which were exacerbated by stress and a poor work environment (lighting/air/noise pollution).

Despite these challenges, I navigated my way through three different jobs and ultimately landed my current role where I work on an amazing team doing exactly the type…

After publishing a blog post about my experience choosing and preparing for data science boot camp, I have gotten many follow up questions, especially ones about life after boot camp. For these people who are considering boot camp, I am hopeful that these blogs and my YouTube channel will help answer some of these burning questions. Though everyone situations differ, I also give some general advice about going to boot camp.

If you have 12 minutes, you can watch me discuss this topic on my YouTube channel. Alternatively, TLDR/TLDW:

TLDR/TLDW, my top advice to prospective boot campers:

1. Establish connections…

Office Hours

I recently made a career transition from artist to data engineer and wanted to share what I learned. By sharing my personal journey, I attempt to give my best advice based on entering the tech field as a newb and I am hopeful that this will help and inspire others.

TDLR, here are my 5 key lessons. Below I elaborate on each in detail.

5 key lessons

Lesson #1: Don’t try to work at a FANG (Facebook-Amazon-Netflix-Google) company just for the prestige or money.

Lesson #2: Don’t apply to a company unless you know their values, products, investments and ethics.

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