Issue #214 - THE ML ENGINEER ??
Alejandro Saucedo
Tech Executive @ Zalando | Chair/Advisor @ UN, ACM, LF, etc | Join 60k+ ML Newsletter
This 214 edition of the ML Engineer newsletter contains curated ML tutorials, OSS tools and AI events for our 15,000+?subscribers. You can access the Web Newsletter Homepage as well as the Linkedin Newsletter Homepage where you can find all previous editions ??
If you like the content please support the newsletter by sharing with your friends via ?? Twitter ,??? Linkedin and??? Facebook !
This week in the ML Engineer:
If you would like to suggest articles, ideas, papers, libraries, jobs, events or provide feedback just hit reply or send us an email to [email protected] ! We have received a lot of great suggestions in the past, thank you very much for everyone's support!
Andrej Karpathy has put together a fantastic 2-hour tutorial where he builds a Generative Pretrained Transformer (GPT). He goes through a step-by-step walkthrough starting from the basics, and following OpenAI's GPT2/GPT3 paper "Attention is All You Need".
Sebastian Raschka on best practices in Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning. This paper contains a comprehensive techniques in ML for essential model evaluation techniques, and covers into foundations such as cross-validation, hyperparam optimization, algorithm comparison, and more.
Google Research on their Deep Learning Tuning Playbook. In collaboration with the Google Brian team, this great resource covers topics relevant for practitioners interested in maximizing the performance in deep learning models, and emphasises the process of hyperparameter tuning techniques and best practices.
The Director of Machine Learning Platform at Chime shares his thoughts on Hidden Tech Debts in Machine Learning system. This interesting article covers 5 key tech debt areas together with suggested mitigation approaches that can be explored.
Golang has become a highly popular language for distributed systems as well as data intensive applications. This article provides a comprehensive overview of the principles, concepts and basics of interacting with a postgres database with the built-in database/sql package.
领英推荐
Upcoming MLOps Events
The MLOps ecosystem continues to grow at break-neck speeds, making it ever harder for us as practitioners to stay up to date with relevant developments. A fantsatic way to keep on-top of relevant resources is through the great community and events that the MLOps and Production ML ecosystem offers. This is the reason why we have started curating a list of upcoming events in the space, which are outlined below.
Conferences we spoke at recently:
Other relevant upcoming MLOps conferences:
Open Source MLOps Tools
Check out the fast-growing ecosystem of production ML tools & frameworks at the github repository which has reached over 10,000 ? github stars. We are currently looking for more libraries to add - if you know of any that are not listed, please let us know or feel free to add a PR. Four featured libraries in the GPU acceleration space are outlined below.
If you know of any open source and open community events that are not listed do give us a heads up so we can add them!
As AI systems become more prevalent in society, we face bigger and tougher societal challenges. We have seen a large number of resources that aim to takle these challenges in the form of AI Guidelines, Principles, Ethics Frameworks, etc, however there are so many resources it is hard to navigate. Because of this we started an Open Source initiative that aims to map the ecosystem to make it simpler to navigate. You can find multiple principles in the repo - some examples include the following:
If you know of any guidelines that are not in the "Awesome AI Guidelines" list, please do give us a heads up or feel free to add a pull request !
About us ? The Institute for Ethical AI & Machine Learning is a UK-based research centre that carries out world-class research into responsible machine learning.