mirsci

[mirsci @mirsci]

#DataPrivacy analysis in the context of #GDPR compliance implemented by @XAIN_AG, as outlined in https://t.co/ds036sSJiB using #FedML #MachineLearning, and having as main goals:

[mirsci @mirsci]

Design for securing an outsourced and #distributed #MachineLearning (as a service) system based on #SGX enclaves, #Ryoan sandboxes, #Theano, from @rzshokri , Congzheng Song, Tyler Hunt, Vitaly Shmatikov, Emmett Witchel

[Software Engineering Papers @ComputerPapers]

Chiron: Privacy-preserving Machine Learning as a Service. https://t.co/rRF2kBhuyp

[mirsci @mirsci]

#Google released Feast, its new open source feature store to manage storage and access of #MachineLearning features https://t.co/xsFqO9dNA3

[Jesus Rodriguez @jrdothoughts]

Introducing Feast https://t.co/hjVgxqVGe1 #deeplearning #machinelearning #datascience #artificialintelligence #InvectorLabs #Google

[statisticallyfit @anamariavintila]

Auto differentiation in Scala code from WinVector: https://t.co/yslIer2MS8

[mirsci @mirsci]

Focus on building first the foundation for data ingestion, #dataflow, transformation and only then on overlaying complex AI models is critical in building sustainable AI products - “The AI Hierarchy of Needs” by @mrogati https://t.co/0xgmn2JYnm

[mirsci @mirsci]

@semanticbeeng , @anamariavintila you may like to check this book https://t.co/QsGxoE3psI

[mirsci @mirsci]

@semanticbeeng have you seen this? https://t.co/YR2kIHwQl8

[Petuum @PetuumInc]

Read about Petuum's solution to the memory limit challenge in #BigData #MachineLearning https://t.co/uJCFYfJY41

[mirsci @mirsci]

Just completed a small POC with Karma #karmausc, led by Pedro Szekely (@szeke) for #semantic data mappings. Does anyone know if Karma platform has a support model for production implementations? Thanks.

[Paweł Szulc @EncodePanda]

Here's a pattern: yet another company I work for is 100% remote and guess what: they have zero issues finding talented people willing to work for them.

Send this tweet to the HR department in your company.

[statisticallyfit @anamariavintila]

Just completed a nice function to return symbolic natural cubic spline polynomials in a vector in Matlab.

[mirsci @mirsci]

@KarmaSemWeb Very impressed with Karma #karmausc, for semantic data mappings, between flat data structures towards #semantic data. Does Karma platform have a support model for production implementations? Thanks.

[Adrian Colyer @adriancolyer]

Serialization and deserialization is a major performance killer in frameworks like Spark and Flink. Skyway bypasses all that and does direct streaming copies from heap to heap across nodes... https://t.co/ulgKT7eRQX

[mirsci @mirsci]

One more reason to embed #functionalprogramming in the #blockchain designs. Excellent post. https://t.co/H03AjUB3Pk

[mirsci @mirsci]

Scalable #Blockchain platform for enterprise adoption using sharding https://t.co/rFlbQqDQmX

[Adrian Colyer @adriancolyer]

"OmniLedger: A secure, scale-out, decentralized ledger via sharding" Kokoris-Kogias et al., 2018 https://t.co/4qkDZBw72j #themorningpaper

Getting to Visa scale with blockchain-based transactions.

[Axionable AI @AxionableAI]

5 Heroic Tools for Natural Language Processing #NLP
1- CoreNLP from #Stanford
2- NLTK library for #Python
3- TextBlob as an interface
4- Gensim for similarity analysis
5- SpaCy to boast performance
https://t.co/aFAfD2xA7C
#DataScience #chatbot #TextMining

[Martin Krasser @mrt1nz]

I wrote a brief summary of courses and books that helped me getting started with (and further into) #MachineLearning #DeepLearning and #BayesianStatistics https://t.co/mvcjnr1kKE