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Automated Machine Learning — A Paradigm Shift That Accelerates Data Scientist Productivity @ Airbnb by
@HamelHusainhttps://medium.com/airbnb-engineering/automated-machine-learning-a-paradigm-shift-that-accelerates-data-scientist-productivity-airbnb-f1f8a10d61f8 …Thanks. Twitter will use this to make your timeline better. Undo -
A vendor-neutral open standard for distributed tracing http://opentracing.io/
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scikit-feature: Open-Source Feature Selection Repository in Python http://featureselection.asu.edu/
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Exploring the Structure of High-Dimensional Data with HyperTools in Kaggle Kernelshttp://disq.us/t/2mhrxvo
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Sean Lin Retweeted
Cool! Google just published an interview about my Machine Learning book, in case you want to get started with ML: https://cloud.google.com/blog/big-data/2017/02/the-book-for-getting-hands-on-with-machine-learning-deep-learning-and-tensorflow …
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Does Balancing Classes Improve Classifier Performance? http://www.win-vector.com/blog/2015/02/does-balancing-classes-improve-classifier-performance/ … 來自
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Sean Lin Retweeted
CodeTengu Weekly - Issue 76 心裡想的是 Microservice,手裡做的是 Distributed Monolith http://weekly.codetengu.com/issues/76
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10 more lessons learned from building Machine Learning systems - MLConf by
@xamat#bigdata#datamininghttp://www.slideshare.net/xamat/10-more-lessons-learned-from-building-machine-learning-systems-mlconf …Thanks. Twitter will use this to make your timeline better. Undo -
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Dealing with imbalanced data: undersampling, oversampling and proper cross-validation - Marco Altini http://www.marcoaltini.com/2/post/2015/08/dealing-with-imbalanced-data-undersampling-oversampling-and-proper-cross-validation.html …
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Sean Lin Retweeted
The lessons we learnt when building
#XGBoost system http://homes.cs.washington.edu/~tqchen/2016/03/10/story-and-lessons-behind-the-evolution-of-xgboost.html … and also see our paper at http://arxiv.org/abs/1603.02754@guestrinThanks. Twitter will use this to make your timeline better. Undo -
Approaching (Almost) Any Machine Learning Problemhttp://blog.kaggle.com/2016/07/21/approaching-almost-any-machine-learning-problem-abhishek-thakur/ …
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Sean Lin Retweeted
ER of Mastering Feature Engineering is out! Rough draft for the first few chapters. Feedback welcome! http://shop.oreilly.com/product/0636920049081.do …
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Sean Lin Retweeted
Our 4th AOSA book "500 Lines or Less" is out! Read for free on web, or buy from
@luludotcom: http://aosabook.org/blog/2016/07/500-lines-or-less-is-available-now/ …pic.twitter.com/MRC0C2VAqV
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Sean Lin Retweeted
Hackable Projects - Pillar 2: Debuggability: By: Patrik Höglund This is the second article in our series on H...http://bit.ly/2e470Hr
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How YouTube's Recommendation Algorithm Workshttps://www.infoq.com/news/2016/09/How-YouTube-Recommendation-Works#.WBjVZmpNCgg.twitter …
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Sean Lin Retweeted
I wrote about how we do service discovery at
@stripe! https://stripe.com/blog/service-discovery-at-stripe …pic.twitter.com/S9UuDiMLLy
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Netflix Zuul Gets a Makeover to a Asynchronous and Non-Blocking Architecturehttps://getpocket.com/@linekin/share/1236804 …
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Spark in Flames – Profiling Spark Applications Using Flame Graphs https://www.paypal-engineering.com/2016/09/08/spark-in-flames-profiling-spark-applications-using-flame-graphs/ …
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New zine: Linux debugging tools you'll love - Julia Evans http://jvns.ca/blog/2016/09/07/new-zine-linux-debugging-tools-youll-love/ … 來自
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