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BigData News Wednesday, June 6

IoT DevOps Hands-On (Day 3): GitLab CI/CD and Friends – DZone IoT

  • In this article, we continue our journey into the world of DevOps and IoT with GitLab CI/CD.
  • But, let’s see how GitLab CI/CD can help us in an IoT device development workflow.
  • Then, we can check the status of our pipelines and jobs from the GitLab CI/CD web interface.
  • Except for Travis CI and GitLab CI/CD, there are plenty of popular CI/CD tools and services out there like TeamCity, CircleCI, Bamboo, Codefresh, Codeship, and the list is endless.
  • So far, we talked about some of the most popular CI/CD tools and whether they fit well in IoT device development.

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IoT DevOps Hands-On (Day 3): GitLab CI/CD and Friends – DZone IoT

Deep Learning based Text Recognition (OCR) using Tesseract and OpenCV

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Deep Learning based Text Recognition (OCR) using Tesseract and OpenCV | Learn OpenCV

Top 10 Machine Learning Algorithms

  • Most of them seem to define top as oldest, and thus most used, ignoring modern, efficient algorithms fit for big data, such asindexation, attribution modeling, collaborative filtering, or recommendation engines used by companies such as Amazon, Google, or Facebook.
  • Some of these techniques such as Naive Bayes (variables are almost never uncorrelated),Linear Discriminant Analysis (clusters are almost never separated by hyperplanes), orLinear Regression (numerous model assumptions – including linearity – are almost always violated in real data)have been so abusedthat I would hesitate teaching them.
  • You might have to attend classes taught by real practitioners (people who worked for big data solutions vendors) to learn modern tools that will give you a competitive edge on the job market.
  • An publisher such as O’Reilly, as well as some universities with an applied data science department, provide good education about these state-of-the-art techniques, with case studies.
  • My upcoming book Data Science 2.0will cover much of the topic, and my previous Wiley bookis a good starting point.

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Top 10 Machine Learning Algorithms

Top Big Data Courses

The Ultimate Hands-On Hadoop - Tame your Big Data! (31,889 students enrolled)

By Sundog Education by Frank Kane
  • Design distributed systems that manage "big data" using Hadoop and related technologies.
  • Use HDFS and MapReduce for storing and analyzing data at scale.
  • Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
  • Analyze relational data using Hive and MySQL
  • Analyze non-relational data using HBase, Cassandra, and MongoDB
  • Query data interactively with Drill, Phoenix, and Presto
  • Choose an appropriate data storage technology for your application
  • Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
  • Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
  • Consume streaming data using Spark Streaming, Flink, and Storm

Learn more.


Taming Big Data with MapReduce and Hadoop - Hands On! (13,894 students enrolled)

By Sundog Education by Frank Kane
  • Understand how MapReduce can be used to analyze big data sets
  • Write your own MapReduce jobs using Python and MRJob
  • Run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce
  • Chain MapReduce jobs together to analyze more complex problems
  • Analyze social network data using MapReduce
  • Analyze movie ratings data using MapReduce and produce movie recommendations with it.
  • Understand other Hadoop-based technologies, including Hive, Pig, and Spark
  • Understand what Hadoop is for, and how it works

Learn more.