- The Case for a Global Responsible AI Framework, by David Sweenor - Oct 30, 2021.
Public and private organizations have come out with their own set of AI principles, focusing on AI-related risks from their perspective. However, it’s imperative d=to have a global consensus on Responsible AI – based on data governance, transparency and accountability – on how to utilize and benefit from AI in a way that is both consistent and ethical.
- How to Build Data Frameworks with Open Source Tools to Enhance Agility and Security, by Nahla Davies - Oct 27, 2021.
Let’s take a look at how to harness open source tools to build your data frameworks.
- How To Defeat The Machine Learning Engineer Impostor Syndrome, by Pau Labarta Bajo - Oct 26, 2021.
How many times have you taken yet another online course on machine learning or read yet another paper on a new emerging topic, to be up-to-date in this crazy fast-paced AI/ML world -- only to keep feeling like an ML engineer impostor? These three personal tips can help you overcome the classic (and common) impostor syndrome behind every emerging ML engineer who wants to be better at what you do.
- Save Sarah Connor with Data Science, by Peter Kozlov - Oct 25, 2021.
Data science and data privacy are deeply interwoven, and must be carefully considered by practitioners. In comparing the Safe Harbour and Expert Determination data obfuscation approaches, Safe Harbour has been very popular among data engineers but has fundamental limitations, where Expert Determination offers important advantages.
- Exclusive: OpenAI summarizes KDnuggets, by Gregory Piatetsky - Oct 23, 2021.
OpenAI has recently done amazing work summarizing full-length books. We have asked OpenAI to summarize two recent KDnuggets posts, and the results have a very human-like quality. Only the last line betrays the inhuman intelligence at work.
- Data Scientist vs Data Engineer Salary, by Matthew Przybyla - Oct 20, 2021.
What are the differences between these two popular tech roles?
- How Data Professionals Can Impress Even When Busy, by Devin Partida - Oct 19, 2021.
While there may be plenty of room for advancement even when busy, how to achieve that isn’t always clear. In that spirit, here are five ways you can impress your company leadership.
- Avoid These Five Behaviors That Make You Look Like A Data Novice, by Tessa Xie - Oct 18, 2021.
If you are new to the Data Science industry or a well-versed veteran in all things data and analytics, there are always key pitfalls that each of us can easily slide into if we are not careful. These behaviors not only make us appear like novices, but they can risk our position as a trustworthy, likable data partner with stakeholder.
- How our Obsession with Algorithms Broke Computer Vision: And how Synthetic Computer Vision can fix it, by Paul Pop - Oct 15, 2021.
Deep Learning radically improved Machine Learning as a whole. The Data-Centric revolution is about to do the same. In this post, we’ll take a look at the pitfalls of mainstream Computer Vision (CV) and discuss why Synthetic Computer Vision (SCV) is the future.
- Will Your Job be Replaced by a Machine?, by Martin Perry - Oct 13, 2021.
Yes! It will happen. However, you can pivot and thrive in this disruptive time by becoming a Citizen Developer!
- How I Built A Perfect Model And Got Into Trouble, by Oleg Novikov - Oct 12, 2021.
Data-driven decisions, actionable insights, business impact—you've seen these buzzwords in data science jobs descriptions. But, just focusing on these terms doesn't automatically lead to the best results. Learn from this real-world scenario that followed data-driven indecisiveness, found misleading insights, and initially created a negative business impact.
- Choose The Right Job in Data: 5 Signs To Look For In An Engineering Culture, by Niv Sluzki - Oct 8, 2021.
Software engineers seeking jobs at data companies face a new problem: choosing the right job out of all the options. Learn the 5 signs that signal an agile and innovative engineering culture.
- Building and Operationalizing Machine Learning Models: Three tips for success, by Jason Revelle - Oct 7, 2021.
With more enterprises implementing machine learning to improve revenue and operations, properly operationalizing the ML lifecycle in a holistic way is crucial for data teams to make their projects efficient and effective.
- Will Data Analysts be Replaced by AI?, by Ngwa Bandolo Bobga Cyril - Oct 5, 2021.
It's the question so many are asking: will data analysts be replaced by AI? Read this well-reasoned and concise opinion by someone with insight into the matter.
- Cartoon: How Deep Is That Data Lake?, by Gregory Piatetsky - Oct 2, 2021.
New KDnuggets Cartoon looks at some of the problems data engineers may encounter when trying to measure data lakes.
- Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?, by Kevin Vu - Oct 1, 2021.
Ever larger models churning on increasingly faster machines suggest a potential path toward smarter AI, such as with the massive GPT-3 language model. However, new, more lean, approaches are being conceived and explored that may rival these super-models, which could lead to a future with more efficient implementations of advanced AI-driven systems.