The future of work is usually associated with two scenarios. Pessimists emphasize fears of possible unemployment, and optimists see it as a new set of jobs. However, what they both agree on is that the form of work will depend on technological progress.Photo by: Robynne HuOver the last two hundred years, technologies have continuously changed the way we work. A steam engine, … [Read more...] about What trends will shape the future of work in the 21st Century?
In this blog post, we shall prove the convexity for the Mean Squared Error Loss function used in a traditional Regression setting.In case you haven’t checked out my previous blog — The Curious Case of Convex Functions, I would highly recommend you do. The blog focuses on the basic building blocks for proving/testing the convexity of a function.With that in mind, let us start by … [Read more...] about Proving Convexity of Mean Squared Error Loss Function
Here comes what you have been looking for!!!!!An end to end explained, beginner-friendly simple linear regression model using Scikit-learn .I have done my best to explain even minute details to make this article comprehensible for every one.FIRST AND FORMOST LET ME GIVE YOU A QUICK UNDERSTANDING ABOUT SCIKIT-LEARN :SciKit-learn is probably the most useful library for machine … [Read more...] about Machine Learning in Python: Building a Simple Linear Regression Model using SciKit-Learn.
ModelOps approach to discover, deploy, manage & govern machine learning at scaleOnly about half of all machine learning models actually get deployed. Far fewer produce real value. Many early adopters have invested millions, but remain unimpressed and discouraged by the lack of returns thus far. For most organizations, getting “out of the lab” and into “production” is too … [Read more...] about ModelOps: The Key to Unlocking the Future of AI