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Stop (and Start) Hiring Data Scientists
Large companies are losing many data scientists to smaller companies, so what should executives and managers do? These three “stop & start” tactics can improve talent retention, and help define a new way of recruiting and working for the Data Science field.
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Top 4 Data Extraction Tools
Data extraction tools give you the boost you need for gathering information from a multitude of data sources. These four data extraction tools will help liberate you from manual data entry, understand complex documents, and simplify the data extraction process.
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4 Tips for Dataset Curation for NLP Projects
You have heard it before, and you will hear it again. It's all about the data. Curating the right data is also so important than just curating any data. When dealing with text data, many hard-earned lessons have been learned by others over the years, and here are four data curation tips that you should be sure to follow during your next NLP project.
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AI Books you should read in 2021
As of late, every year seems to be a "break-out" year for AI. So, it's time for you to get ready for the future in the age of automation. This collection of books will help you prepare for the many opportunities to come, many of which may not have yet been imagined.
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These Soft Skills Can Make or Break Your Data Science Career
In an industry long ruled by hard skills, the future career success of tomorrow’s data scientists might well depend on their ability to deploy a variety of soft skills into the workplace.
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How to pitch to VCs, explained: The Deck We Used to Raise Capital For Our Open-Source ELT Platform
Winning seed funding from venture capitalists is a daunting task, and the pitch is key. Learn how one effective slide deck resulted in a successful early funding round for an open-source start-up, Airbyte.
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Awesome list of datasets in 100+ categories
With an estimated 44 zettabytes of data in existence in our digital world today and approximately 2.5 quintillion bytes of new data generated daily, there is a lot of data out there you could tap into for your data science projects. It's pretty hard to curate through such a massive universe of data, but this collection is a great start. Here, you can find data from cancer genomes to UFO reports, as well as years of air quality data to 200,000 jokes. Dive into this ocean of data to explore as you learn how to apply data science techniques or leverage your expertise to discover something new.
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 A checklist to track your Data Science progress
Whether you are just starting out in data science or already a gainfully-employed professional, always learning more to advance through state-of-the-art techniques is part of the adventure. But, it can be challenging to track of your progress and keep an eye on what's next. Follow this checklist to help you scale your expertise from entry-level to advanced.
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6 side hustles for an aspiring data scientist
As an aspiring data scientist or an employed professional, many opportunities exist for you to offer your skills to a broader audience through side gigs. While the difficulty and risk vary, experiences from applying your data science practice to areas outside your immediate career path can increase your expertise while even increasing your bank account.
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Feature stores – how to avoid feeling that every day is Groundhog Day
Feature stores stop the duplication of each task in the ML lifecycle. You can reuse features and pipelines for different models, monitor models consistently, and sidestep data leakage with this MLOps technology that everyone is talking about.
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A checklist to track your Data Science progress