Terence

Terence Davies was the great British movie artist of working class Catholic experience and gay identity, a passionate believer and practitioner of cinema. And was also a wonderfully stylish and self-assured presence in person, with a gorgeously resonant voice that might have belonged to a stage matinee idol.I raised a glass of rose with a beaming Davies and Mark Cousins at the 2008 Cannes film festival after the triumphant premiere of Of Time and the City, Davies’s wonderful, personal docu-collage about his home city of…

It is 41 years since US trumpeter Terence Blanchard first took to the stage at London’s Ronnie Scott’s. In 1982, Blanchard was a young upstart from New Orleans touring fast-paced bebop and heady swing with elder statesman Art Blakey. In the years since, he has established his own incisive tone on the horn, regularly collaborating with Herbie Hancock, as well as earning two Oscar nominations for his Spike Lee film scores and, in 2021, becoming the first Black composer have an opera at New York’s Metropolitan with Fire Shut…

Intuitive explanations of the most popular machine learning modelsFirst prize vector created by jcomp — www.freepik.comFor the past few years, I’ve compiled what I believed were the most important machine learning algorithms based on my experiences at work, my conversations with other data scientists, and what I read online.This year, I want to expand on last year’s article by providing more types of models, as well as more models within each category. Through this, I hope to provide a repository of tools and techniques…

A comprehensive guide to industry leading clustering techniquesPhoto by Mel Poole on UnsplashK-means clustering is arguably one of the most commonly used clustering techniques in the world of data science (anecdotally speaking), and for good reason. It’s simple to understand, easy to implement, and is computationally efficient.However, there are several limitations of k-means clustering which hinders its ability to be a strong clustering technique:K-means clustering assumes that the data points are distributed in a…

A newer and more effective approachPhoto by Ales Krivec on UnsplashTwo years ago, I wrote a similar article explaining how I’d learn data science if I could start over. Now that I’m four years into my career, which is double the amount of time, I’ve realized that there is a much better approach to learning data science.The problem with my previous guide is that it acts as a one-size-fits-all solution which simply isn’t the case. Because data science covers such a broad spectrum of skills and subjects, it’s only natural…

Awesome visualizations on the Ukraine War, Inflation, and more!Image by svstudioart on FreepikLast year I shared what I thought were ten of the best data visualizations from 2021. I’m back again with ten of the best data visualizations from 2022!Similar to last year, I wanted to share a variety of types of data visualizations, and also ones that were relevant with particular events that happened this year.Let’s dive into it!Be sure to subscribe here to never miss another article on data science guides, tricks and tips,…

Photo by Jonathan Chng on UnsplashThings move VERY quickly in the world of data science. In my career alone (the past ~4 years), I’ve had to learn several new, industry-leading tools like Prophet, dbt, and Dash Plotly.Being a data scientist means that you have to continuously learn new skills and tools to broaden your arsenal of tools and also keep up with industry leading platforms.In this article, I wanted to share with you all of the resources and hidden gems that I use to stay up-to-date with data science! With that…

Common mistakes to look out for in your careerPhoto by 愚木混株 cdd20 on UnsplashOne of the hardest things about working with data is dealing with the fallacies and biases that plague both the data itself as well as how we interpret the data. Because of the hundreds of biases and fallacies that exist, most of us are guilty of making false conclusions and creating biased models.In this article, I wanted to talk about 5 of the most common biases and fallacies that all data scientists should look out for and how to actually…

Expand your arsenal of data skills and tools with these visualizationsControl panel vector created by storyset — www.freepik.comWhile everyone glorifies machine learning models and intricate neural networks, many forget the immense value that one can get from building a powerful data visualization. And I’m not talking about basic visualizations like line graphs and bar charts.In this article, I’m going to share with you five powerful data visualizations that you should know how to build because they are extremely powerful…

Tips to optimize your data science careerPhoto by JESHOOTS.COM on UnsplashWhile money isn’t the sole motivating factor that drives me to advance myself in my career, I’d be lying if I said it wasn’t a factor at all. As I approach my fifth year in my data science career, I’ve realized several factors that accelerated my progression and income.And so, I wanted to share with you some tips that I believe will help you advance yourself in your data science career! Keep in mind that these points are more anecdotal than…