The best data science and machine learning articles. Written by data scientist for data scientist (and business people)
Peer reviewed by Kat Holmes — Data Director ITVAs businesses recognize the decisive power of data to achieve business goals, most are hoping to put data in the driver’s seat of their business and product strategies. This entails putting together ...
You've probably heard a lot about data science, artificial intelligence and big data. Frankly, there has been a lot of hype around these areas. What it has done is inflate expectations about what data science and data can actually accomplish. Over...
In this blog post we will talk about the democratization of data in the financial sector. The format will be a bit different than usual, as it is an interview with our CEO Dimitry Kushelevsky given to PrivacyLabs.ai. The interview was given in Pod...
From a company perspective, data science projects should always be viewed as experiments. Remember that we are talking about science, and science bases many of its theories on the results of a series of experiments. From here, many companies start...
I'm often asked, "what kind of machine learning project should I work on?"And I usually answer with "follow your curiosity."Why?Because of how experimental machine learning is, it's in your best interest to figure things out through tinkering. By ...
Hello everyone, I'm Daniel Morales co-founder of DataSource.ai and today I want to share with you very good news and the new advances we are making in order to have an excellent data scientist community globally. New CEOThis is perhaps the most im...
Finance and economics are becoming more and more interesting for all kinds of people, regardless of their career or profession. This is because we are all affected by economic data, or at least we are increasingly interested in being up-to-date, a...
Open innovation is a term used to promote a different and open mindset towards innovation that goes against the secrecy and traditional mentality of corporate R&D labs. The use of the term "open innovation" refers to the growing acceptance of ...
The data is sometimes called the "new oil," a newly discovered source of wealth that is extracted from the depths of corporate and government archives. Some accountants are so excited about the potential value of the data that they count it in the...
Startup, SMB or company founders, managers or decision makers often claim that they are "data rich but information poor". This statement is in many cases only partially correct because it hides a misconception about the data life cycle. The fact t...
Today, large companies have large I+D budgets that allow them to experiment and be at the cutting edge of new technologies; always adopting the newest, trying to adapt it to their own needs, trying to find the hidden value in each of them. It is n...
As usual, we have given ourselves the task of interviewing the winners of the competition "Google Play Store Rating Prediction" that ended a few days ago, having as winner Edimer "Siderus" from Colombia and with a score of 0.698709403908066 and wh...
A plethora of online courses and tools promise to democratize the field, but just learning a few basic skills does not a true data scientist makeEvery few years, some academic and professional field gets a lot of cachet in the popular imagination....
No matter the size or the industry, there is simply no excuse not to implement Business Intelligence, even more so when we are in the age of data science and artificial intelligence. Because Business Intelligence or BI allows us to make smarter bu...
The data science community exists to facilitate the exchange of information, resources and stimuli among the data science community.We believe that our mission is best accomplished in a friendly, safe and welcoming environment; free from intimidat...
Insights from conversations with DS recruiters.Preparing for a good Data Science resume for an interview or a networking event never gets easy, does it? There is a significant amount of learning, exploration, understanding, and analysis that goes ...
This is the second post of a series I’m writing about dialogues from my company’s internal Slack group. You can check out the first one here.If you’re joining us now, we run a private Slack group that’s half experienced data scientists, and half a...
Because who needs data?Photo by Nick Coleman on UnsplashI think the title is pretty clear, so let’s get straight to it.#1: You don’t have any dataBefore even thinking about hiring a data scientist, you should step back and consider your data.A dat...
A complete hands-on guide to the best practices and concepts of visualization in python using matplotlib, pyplot, and seabornPhoto by William Iven on UnsplashBusiness Intelligence, BI is a concept that usually involves the delivery and integration...
10 Practical Tips on how to get employed as a Data Scientist as soon as you graduate.Image by StartupStockPhotos from PixabayYou have worked hard for several months to learn the ’ins and outs’ of statistics and programming, and you have remembered...