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The Events Must Flow: Lessons Learnt Evolving the Spotify’s Event Delivery System
Nelson Arape discusses the evolution of the Spotify’s Event Delivery System and the lessons learned along the way.
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Deep Learning for Recommender Systems
Oliver Gindele discusses how some DL models can be implemented in TensorFlow, starting from a collaborative filtering approach and extending that to more complex deep recommender systems.
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Putting the Spark in Functional Fashion Tech Analytics
Gareth Rogers shows how his team used Clojure to provide a solid platform to connect and manage an AWS hosted analytics pipeline and the pitfalls they encountered on the way.
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Reinforcement Learning: A Gentle Introduction with a Real Application
Christian Hidber shows “how” and “why” Reinforcement Learning works, using as a practical example siphonic roof drainage.
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Comparing Machine Learning Strategies Using Scikit-Learn and TensorFlow
Oliver Zeigermann looks at different ML strategies -KNN, Decision Trees, Support Vector Machines, and Neural Networks- and visualizes how they make predictions by plotting their decision boundaries.
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How to Create a Data Science Product from Scratch?
Dmytro Bilash discusses the top five biggest challenges in creating a data science product, compares a product for one client and a scalable one for the whole market, and how to be successful.
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Apache Metron in the Real World – Big Data and Cybersecurity, a Perfect Match
Dave Russell takes a look at a number of different organizations who are on their big data cybersecurity journey with Apache Metron.
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Docker Data Science Pipeline
Lennard Cornelis explains why they chose OpenShift and Docker to connect to the Hadoop environment, also how to set up a Docker container running a data science model using Hive, Python, and Spark.
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Productionizing H2O Models with Apache Spark
Jakub Hava demonstrates the creation of pipelines integrating H2O machine learning models and their deployments using Scala or Python.
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Data Science for Lazy People, Automated Machine Learning
Diego Hueltes discusses using Automated Machine Learning as a personal assistant in Data Science.
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Winning Ways for Your Visualization Plays
Mark Grundland explores practical techniques for information visualization design to take better account of the fundamental limitations of visual perception.
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