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Could Your Machine Learning Model Survive the Crisis: Monitoring, Diagnosis, and Mitigation Part 1
As the world is changing rapidly around us, it is often questionable whether something we learned from the past is still valid. Machine learning models that make predictions of the future based on past data points are probably under most scrutiny from businesses in the current... Read more
Building a Production-Level Data Pipeline Using Kedro
How can Kedro help you? Suppose you are a self-taught data scientist who does not have much experience in software development. One morning, your senior executive asks you to provide an ad-hoc analysis – perks of the job, and when you do, she thanks you for... Read more
From Good to Great: The 5 Skills You Need to Shine in Data Science
Almost three years ago, I switched from a career in academia to a career in business in a data science role. This used to be somewhat of a rare event, but today it is commonplace: not only is there a shortage of data scientists, but also... Read more
How to Explain Your ML Models?
Explainability in machine learning (ML) and artificial intelligence (AI) is becoming increasingly important. With the increased demand for explanations and the number of new approaches out there, it could be difficult to know where to start. In this post, we will get hands-on experience in explaining... Read more
Autograd is PyTorch’s automatic differentiation package. Thanks to it, we don’t need to worry about partial derivatives, chain rule, or anything like it. To illustrate how it works, let’s say we’re trying to fit a simple linear regression with a single feature x, using Mean Squared... Read more
Outliers in Data Science: To Be or Not to Be an Anomaly?
An outlier may be defined as an object that is out of ordinary, which differs significantly from the norm. In day to day examples, it could be a baby panda among adult pandas, a champion breaking a world record, or fraud emails in your inbox. Why... Read more
Continuous Delivery for Machine Learning
Why is bringing machine learning code into production hard? Machine Learning applications are becoming popular in all industries. However, the process for developing, deploying, and continuously improving them is more complex compared to more traditional software, such as a web service or a mobile application. These... Read more
Reportingonsuicide.cisco.com: Interview with Team Member Dr. Annie Ying
Last year, I established Cisco’s Data Science and AI for Good initiative as a channel for Cisconians to give back pro bono, using their professional expertise to help nonprofits make the world a better place through data and analytics. Almost a year later, in collaboration with... Read more
Reportingonsuicide.cisco.com: Interview with Team Member Edgar Murillo
Last year, I established Cisco’s Data Science and AI for Good initiative as a channel for Cisconians to give back pro bono, using their professional expertise to help nonprofits make the world a better place through data and analytics. Almost a year later, in collaboration with... Read more
Data Science: Dare to Start Simple
Imagine that you are the first data scientist in a company, maybe in the industrial field, in one of the old industries or old economy branches. Then, you are a unicorn. Basically, you start data science from scratch: you must introduce, explain, promote, and establish data... Read more