All Hands on Data #83
We are introducing All Hands on Data in video form this week along with the normal version. If you'd prefer to listen versus read about some great data articles, click that play button!
Data Science Scholarships 2024: Find the Best Options
It's a new year! Perhaps you made a resolution to seek some higher education? If so, this is the article for you. Kashettar provides information about scholarship opportunities for women and terminal-degree seekers. - Katt Baum
What is a Business Intelligence Analyst?
I may have cheated here a bit. I’m sharing a video instead of a post, but I think Tighe shares some great information on what a BI Analyst does on a day to day basis. She also outlines some tips on how to land a role in that field if you are looking to break into the field! - Steven Johnson
Samsung or Apple: Which laptop is better for data analytics
As an avid fan of any "Apple vs" debate, this article takes an analytic workflow approach to which laptop is "better" for data professionals. Curious to find out what the verdict is? Check it out - Angel Catalan
Data Engineering with ... match
I was first introduced to the match statement when I started learning Rust, and was reluctant to use it at first. My thoughts were similar to the "old little hobbit" described in the first paragraph: Why do I need this, I can write the same thing using if-else. The match statement can offer a bit more readability as well as expressiveness (depending on the context), without needing to delve into nested if-else statements. It's true that you can use if-else in any situation where you would normally use match, but the evaluation should come down to readability and maintainability. - Wes Poulsen
Building a High-Performing Data Science Team: Tips and Tricks for Success
While most articles focus on the tools and systems in data science, this one dove more heavily into the team side of things. One of the big takeaways is that while data science and machine learning teams are writing code, they are not application developers. They have their own process, cadence, and delivery cycle that management needs to understand to successfully integrate them into the broader enterprise. - John Forstmeier
Google, MIT's SynCLR: Model Training Using Only Synthetic Data
This is an innovative approach of training AI image models solely with synthetic data, utilizing advanced AI models like Meta's Llama and OpenAI's GPT-4 which reduces the dependency on real world data - Johnathan Rodriguez