The CACE principle and why technical debt in ML is different. Technical debt is a concern in Software Engineering, but also increasingly in Machine Learning. There are many pitfalls to look for, and principles to follow.
Technical debt. If those words have not provoked a shiver down your spine, you might be too novice, or you have entirely given up. In a recent paper¹, a team of Google researchers discuss the technical debt hiding in Machine Learning (ML) Systems.
ML allows us to build useful complex prediction systems quickly, but this does not come for free. The authors remark the technical debt framework can uncover massive ongoing maintenance costs in ML systems such as:
Developing and deploying ML is nowadays inexpensive, but there is another part to the equation: maintenance over time. This turns out to be difficult and expensive, and it gets worse if technical debt is left unchecked.
Best Free Resources to Learn Programming, Software Engineering, Machine Learning, And More All you need to learn. Do you know that you can take the courses from MIT, Stanford.
Find out here. Although data science job descriptions require a range of various skillsets, there are concrete prerequisites that can help you to become a successful data scientist. Some of those skills include, but are not limited to: communication, statistics, organization, and lastly, programming. Programming can be quite vague, for example, some companies in an interview could ask for a data scientist to code in Python a common pandas’ functions, while other companies can require a complete take on software engineering with classes.
Machine Learning Engineer vs Data Scientist (Is Data Science Over?) vs Data Analyst vs Research Scientist vs Applied Scientist vs…
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
What is the most important thing to do after you got your skills to be a data scientist? It has to be to show off your skills. Otherwise, there is no use of your skills. If you want to get a job or freelance or start a start-up, you have to show off your skills to people effectively.