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Explainable Artificial Intelligence (XAI) for AI & ML Engineers

Analytics Vidhya

Introduction Hello AI&ML Engineers, as you all know, Artificial Intelligence (AI) and Machine Learning Engineering are the fastest growing filed, and almost all industries are adopting them to enhance and expedite their business decisions and needs; for the same, they are working on various aspects […].

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Explosive growth in AI and ML fuels expertise demand

AI News

AI and machine learning are reshaping the job landscape, with higher incentives being offered to attract and retain expertise amid talent shortages. According to a recent report by Harnham , a leading data and analytics recruitment agency in the UK, the demand for ML engineering roles has been steadily rising over the past few years.

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ML Engineering is Not What You Think — ML Jobs Explained

Towards AI

Last Updated on April 11, 2024 by Editorial Team Author(s): Boris Meinardus Originally published on Towards AI. How much machine learning really is in ML Engineering? But what actually are the differences between a Data Engineer, Data Scientist, ML Engineer, Research Engineer, Research Scientist, or an Applied Scientist?!

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The 7 Most Important Skill Sets for ML Engineers

Towards AI

Last Updated on July 3, 2024 by Editorial Team Author(s): Boris Meinardus Originally published on Towards AI. What are the most important skills for an ML Engineer? So, in this blog post, I want to share the 7 most important skill sets you might need to know if you want to become an ML engineer.

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Go from Engineer to ML Engineer with Declarative ML

Flipboard

Learn how to easily build any AI model and customize your own LLM in just a few lines of code with a declarative approach to machine learning.

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Edge Impulse Launches “Bring Your Own Model” for ML Engineers

Towards AI

Last Updated on April 4, 2023 by Editorial Team Introducing a Python SDK that allows enterprises to effortlessly optimize their ML models for edge devices. Edge Impulse is known for its innovative tools that have greatly lowered the barrier to building edge AI solutions for digital health and industrial productivity.

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We employed ChatGPT as an ML Engineer. This is what we learned

Towards AI

Author(s): Eric Landau, Co-founder and CEO, Encord TLDR; Among the proliferation of recent use cases using the AI application ChatGPT, we ask whether it can be used to make improvements in other AI systems. We test it on a practical problem in a modality of AI in which it was not trained, computer vision, and report the results.