Roger Donaldson’s new film McLaren tells the story of Bruce McLaren’s determination to make it to the summit of global motor racing before his name became synonymous with the sport.
Hi, I'm Fuzzy.
This site, Fuzzy's Logic, is a dumping ground for things I find interesting. If you're looking for content I've personally generated you might want to head directly to one of my other sites:
In software engineering, a software design pattern is a general reusable solution to a commonly occurring problem within a given context in software design. It is not a finished design that can be transformed directly into source or machine code. It is a description or template for how to solve a problem that can be used in many different situations.
Django is an extremely popular and fully featured server-side web framework, written in Python. The module shows you why Django is one of the most popular web server frameworks, how to set up a development environment, and how to get started with using it to create your own web applications
All of this leads to my final big point: “drug problems” are really “society problems.” Consider the current opiate crisis. Do you know when authorities in Ohio, where I reside, became convinced that Ohio had an opiate problem? When opiate deaths began to approach, and then surpassed, the number of car crash deaths in a year. This raises an important question: why are we so tolerant of car-crash deaths, so much so that their frequency has become our baseline for unacceptable accidental death in America?
There has been a recent surge in popularity of Deep Learning, achieving state of the art performance in various tasks like Language Translation, playing Strategy Games and Self Driving Cars requiring millions of data points. One common barrier for using deep learning to solve problems is the amount of data needed to train a model. The requirement of large data arises because of the large number of parameters in the model that machines have to learn.
When working on a problem specific to your domain, often the amount of data needed to build models of this size is impossible to find. However models trained on one task capture relations in the data type and can easily be reused for different problems in the same domain. This technique is referred to as Transfer Learning.