• Ta-Nehisi Coates leads diverse group of MacArthur ‘genius’ grant recipients | US news | The Guardian
• Maths whizz solves a master’s riddle : Nature News & Comment
• On Quitting: — Linda Eliasen
• The ultimate iPhone camera comparison: How does the iPhone 6s camera compare to every other iPhone generation? ~ snap snap snap
• Pattern Recognition and Machine Learning (Information Science and Statistics): Christopher Bishop: 9780387310732: Amazon.com: Books
  Bishop
• Pattern Recognition and Machine Learning | Christopher Bishop | Springer
• Machine Learning in Action: Peter Harrington: 9781617290183: Amazon.com: Books
• An Introduction to Statistical Learning
  with applications in R
• Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
  Trevor Hastie
  Robert Tibshirani
  Jerome Friedman
• Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series): Daphne Koller, Nir Friedman: 8601401113034: Amazon.com: Books
  Koller and Friedman
• Why I Fucking Hate Unicorns and the Culture They Breed | Bothsides of the Table
• Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters
  Spark
• MillWheel: Fault-Tolerant Stream Processing at Internet Scale
  MillWheel: Fault-Tolerant Stream Processing at
  Internet Scale
• Why local state is a fundamental primitive in stream processing – O’Reilly Radar
  What do you get if you cross a distributed database with a stream processing system?
• Apache Flink: Scalable Batch and Stream Data Processing
  Flink’s core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams.

  Flink includes several APIs for creating applications that use the Flink engine:

  DataSet API for static data embedded in Java, Scala, and Python,
  DataStream API for unbounded streams embedded in Java and Scala, and
  Table API with a SQL-like expression language embedded in Java and Scala.
  Flink also bundles libraries for domain-specific use cases:

  Machine Learning library, and
  Gelly, a graph processing API and library.
  You can integrate Flink easily with other well-known open source systems both for data input and output as well as deployment.

• Questioning the Lambda Architecture – O’Reilly Radar
  Questioning the Lambda Architecture
  The Lambda Architecture has its merits, but alternatives are worth exploring.

  by Jay Kreps |@jaykreps | +Jay Kreps | Comments: 19 | July 2, 2014

• Storm, distributed and fault-tolerant realtime computation
  Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm is simple, can be used with any programming language, and is a lot of fun to use!

  Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

• How to beat the CAP theorem – thoughts from the red planet – thoughts from the red planet
  lambda architecture
• Nomad by HashiCorp
  Easily deploy applications at any scale

  A Distributed, Highly Available, Datacenter-Aware Scheduler

• hashicorp/nomad
  A Distributed, Highly Available, Datacenter-Aware Scheduler https://www.nomadproject.io/
• thingCharger
• The world beyond batch: Streaming 101 – O’Reilly Radar
  Tyler’s blog post

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