One thing that we have covered a lot in Smart Data Collective is how artificial intelligence helps businesses protect and improve supply chains. You can
Category: Data Science
In our previous tutorials, you’ve built a solid foundation in PySpark fundamentals—from setting up your development environment to working with Resilient Distributed Datasets and DataFrames.
The image that stopped you mid-scroll today, a hyper-realistic portrait of a historical figure, a fantastical landscape bathed in impossible light, or even a seemingly
want to be machine learning engineers. I get it. It’s a great job, with interesting work, great pay, and overall, it’s very cool. However, it’s
Video content is an essential medium for communication in the digital world. Whether it’s for educational purposes, entertainment, or marketing, video has a unique ability
Not too long ago, business decisions relied heavily on intuition, experience, and a fair bit of guesswork. Today, that guesswork is being replaced with granular,
AI is rewriting the day-to-day of data scientists. , data scientists must learn how to improve productivity and unlock new possibilities with AI. Meanwhile, this
tools like dbt make constructing SQL data pipelines easy and systematic. But even with the added structure and clearly defined data models, pipelines can still
your anomaly detection results to your stakeholders, the immediate next question is always “why?”. In practice, simply flagging an anomaly is rarely enough. Understanding what went
Image by Author | Canva If you like building machine learning models and experimenting with new stuff, that’s really cool — but to be