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THE ML ENGINEER 🤖
Issue #71
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This week in Issue #71:
If you would like to suggest articles, ideas, papers, libraries, jobs, events or provide feedback just hit reply or send us an email to a@ethical.institute! We have received a lot of great suggestions in the past, thank you very much for everyone's support!
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The next generation of young innovators took the virtual channels this weekend to build solutions to tackle the challenge of our generation at the YouthVsCOVID TeensInAI Hackathon. During this event we presented a talk that covered a practical introduction to responsible AI, where we covered some of the key motivations for following best practices to ensure responsible development, deployment and operation of AI systems. Please also check out the other fantastic talks presented at the event at the TeensInAI Youtube Channel.
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A simulation is a representation of a real-world system. One can use mathematical or computational models of this system to study how it works - this article showcases how you can leverage Python's SimPy library to get started.
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SpaCy Co-founder Ines Montani has put together an official advanced NLP course which introduces core Natural Language Processing concepts using SpaCy. This course is broken down into four chapters which cover foundational pieces such as finding workds / phrases, scaling analysis, building processing pipelines and training your own neural network model.
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Every year, Class Central publishes rankings of the world’s highest rated and most popular online courses. This year they decided to showing all the free online courses from some of the top courses at universities (with a section focusing on computer science). This article provides the methodology (and jupyter notebook) used to rank the universities using the central class database.
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The Data Exchange comes back with an excellent podcast where it dives into the trending topic of computational modelling and simulations of epidemic infectionus diseases. During this podcast Chief Scientist Ben Lorica speaks with Data Scientist Bruno Goncalves, and covers some key techniques used for epidemic modelling, as well as their impact in decision making.
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[Updated List 26/04/2020] Due to the current global situation, a large number of conferences have had to face hard choices, several which decided going fully virtual. This hard choice has now open the doors to people from around the world to gain access to the great online content generated by expert speakers and contributors. We wanted to highlight some of these key conferences so they are not missed - these include:
Did we miss any? Please let us know by replying to the newsletter email or by simply emailing us at a@ethical.institute
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The topic for this week's featured production machine learning libraries is Data Visualisation. 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. The four featured libraries this week are:
- Microsoft SEAL - Microsoft SEAL is an easy-to-use open-source (MIT licensed) homomorphic encryption library developed by the Cryptography Research group at Microsoft.
- PySyft - A Python library for secure, private Deep Learning. PySyft decouples private data from model training, using Multi-Party Computation (MPC) within PyTorch.
- Tensorflow Privacy - A Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy.
- TF Encrypted - A Framework for Confidential Machine Learning on Encrypted Data in TensorFlow
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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 thiese 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. We will be showcasingitg three resources from our list so we can check them out every week. This week's resources are:
- ACM's Code of Ethics and Professional Conduct - This is the code of ethics that has been put together in 1992 by the Association for Computer Machinery and updated in 2018
- From What to How - An initial review of publicly available AI Ethics Tools, Methods and Research to translate principles into practices
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About us |
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The Institute for Ethical AI & Machine Learning is a UK-based research centre that carries out world-class research into responsible machine learning systems.
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© 2018 The Institute for Ethical AI & Machine Learning
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