The importance of developing a solid data visualization skillset cannot be understated. The ability to translate your analysis into an effective visual that others can quickly interpret can be the difference between leaving your audience with meaningful insights and leaving them confused. This sounds like a straightforward task, but many…

While SaaS has been around for a while, it seems that this branch of cloud computing is only becoming more and more popular. With a market that’s expected to grow to 145 Billion in USD by 2022, it’s worth paying attention to this increasingly viable model for organizations. …

As the data science sphere continues to grow, so do the branches and technologies within it. Especially given the context of the pandemic, the area is seeing an explosion of new opportunities (and threats) that are worth analyzing. Let’s look at five important topics in the field: 1. Adversarial Machine…

As I learn more about data science, I find that there’s many terms tossed around interchangeably. As someone new to the field, this makes it hard to solidify certain concepts. When it comes to database management and storage, SQL is almost always part of the conversation, but is SQL the…

Data privacy and lack of transparency in terms of how one’s data is shared is a huge ethical concern in the data science community. As more and more personal data is collected and stored through online sources, control over what information is shared and how it will be used has…

The explosion of the data science field has created many opportunities to conduct predictive analysis through the use of advanced machine and deep learning models. Since these approaches are quantitative in nature, sometimes we take data driven insights as facts, but fail to recognize that not everything is so black…

Given the recent political context, various organizations are exploring the use of machine learning to fight political bias in text content, such as news articles and social media posts. While its easy to point to bias in the news sources themselves, it is becoming more common to detect bias in…

In the supervised learning branch of machine learning, there are regression tasks and classification tasks. While regression seeks to answer questions on a continuous scale (ie How much will this house with these features cost?), classification seeks to group our information into predetermined categories. For example, will this person default…

Performing a regression is an incredibly important tool for data scientists and analysts in order to better understand how features impact a certain variable, and make new predictions based on data. While a regression analysis is an iterative process (meaning that you will have to jump back and forth between…