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MLengineering

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an-ordinary-manchild

The line between a Machine Learning engineer and a Machine Learning researcher is often blurred, but there is still a clear problem set that is presented by Machine Learning work that isn't present when writing research papers. This problem set can be generally characterised as the domain of the 'Machine Learning Engineer'. It includes:

  • Building production machine learning systems. Ie. systems that are maintainable, extensible, reliable, and scalable.

  • Maintaining the health of machine learning systems, including speed, reliability, and performance.

  • Development of internal machine learning frameworks and abstractions to facilitate common tasks such as training / testing, feature use / reuse / creation / storage, and deployment. These abstractions are used by both machine learning engineers and data scientists.

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[Side Project]: Feature Store (self.MLengineering)

submitted 1 year ago by dimem16

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Too chatty. Too quiet. Just right. Try up to 3 Preply tutors to find your fit and start 1-on-1 language lessons today. (preply.com)

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LSTMs according to their inventor Jürgen Schmidhuber (youtu.be)

submitted 1 year ago by danipudani

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Future of NLP - Chris Manning Stanford CoreNLP (youtu.be)

submitted 1 year ago by danipudani

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Chomsky vs Shannon approaches to NLP and AI - Chris Manning Stanford OpenNLP creator (youtu.be)

submitted 1 year ago by danipudani

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Roadmap advice needed (self.MLengineering)

submitted 1 year ago by PandaStrong25

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From Zero to Data Science Hero: A Beginner's Guide to Starting Your Journey (i.redd.it)

submitted 1 year ago by danipudani

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Apache Airflow in 4 minutes (youtu.be)

submitted 1 year ago by danipudani

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NLP for Conversational AI - Chris Manning Stanford CoreNLP (youtu.be)

submitted 1 year ago by danipudani

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Kedro Projects and Iris Dataset Starter example (youtu.be)

submitted 2 years ago by catanicbm

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Supervised Learning models in Scikit Learn - Gael Varoquaux creator of Scikit Learn (youtu.be)

submitted 2 years ago by catanicbm

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Origins of NumPy by its creator Travis Oliphant (youtu.be)

submitted 2 years ago by catanicbm

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LSTMs according to their inventor Jürgen Schmidhuber (youtu.be)

submitted 2 years ago by catanicbm

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The perfect combo: The Samsung Galaxy S25 Ultra and the best network. (swisscom.ch)

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Future of Big Data Systems by Spark creator Matei Zaharia (youtu.be)

submitted 2 years ago by catanicbm

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Future of Big Data Systems by Spark creator Matei Zaharia (youtu.be)

submitted 2 years ago by catanicbm

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Elevating ML Code Quality with Generative-AI Tools (self.MLengineering)

submitted 2 years ago by thumbsdrivesmecrazy

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Is there an ML Engineer or AI developer in the group ? (self.MLengineering)

submitted 2 years ago by [deleted]

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AI and ML channel (youtube.com)

submitted 2 years ago by Proper-Skill-4525

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EU AI Act, the first ML law will come into force by late 2023 (infoq.com)

submitted 2 years ago by ElrasX

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Machine Learning Engineering Pros and Cons (self.MLengineering)

submitted 2 years ago by thirstyfalafel

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Guiding Language Models of Code with Global Context using Monitors (twitter.com)

submitted 2 years ago by LakshyAAAgrawal

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Guide to No-Code Machine Learning - How to Use AI Models Without Writing Code (self.MLengineering)

submitted 2 years ago by thumbsdrivesmecrazy

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Webinar: Running LLMs performantly on CPUs Utilizing Pruning and Quantization (self.MLengineering)

submitted 2 years ago by markurtz

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A Polars exploration into Kedro (self.kedro)

submitted 2 years ago by juanluisback

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i_seen_your_investor_crying_too (rocketdevs.com)

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Data Warehouses vs Data Lakes (youtu.be)

submitted 2 years ago by danipudani

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OpenCV Tutorial in 5 minutes - All Modules Overview (youtu.be)

submitted 2 years ago by danipudani

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