In a previous post we looked at root-finding methods for single variable equations. In this post we’ll look at the expansion of Quasi-Newton methods to the multivariable case and look at one of the more widely-used algorithms today: Broyden’s Method.

# Tag: optimization

## Root-Finding Algorithms Tutorial in Python: Line Search, Bisection, Secant, Newton-Raphson, Inverse Quadratic Interpolation, Brent’s Method

**Motivation**

How do you find the roots of a continuous polynomial function? Well, if we want to find the roots of something like:

## Understanding Facebook Ads: Pros and Cons

I recently did some A/B testing work through the Facebook advertising platform, and gave a quick presentation on the pros and cons of the platform. Here’s a summary.

**PRO**

- Microtargeting
- Optimization
- Inexpensive, low ceilings
- Demonstrated to work at scale, sophisticated distribution

**CON**

- Click bots
- Opaque

To clarify my perspective on the platform, some background on the work we did:

We ran some A/B tests through the platform targeting a specific population, evaluating different levels of resulting engagement for statistical significance. I assure you, nothing fancy. Continue reading “Understanding Facebook Ads: Pros and Cons”