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August 2018 Blog Posts (94)

Machine Learning with C++ - Classification with Dlib

Dlib is an open source C++ framework containing various machine learning algorithms and many other complementary stuff which can be used for image processing, computer vision, linear algebra calculations and many other things. It has very good documentation and a lot of useful examples. In this post I will show how to use this library for solving a classification problem on Iris data…


Added by Kyrylo Kolodiazhnyi on August 7, 2018 at 7:03am — No Comments

How you can stay up to date with your #AI and #MachineLearning knowledge


Andrew Ng is a great fan of reading research papers as a long term investment in your own study (On Life, Creativity, And Failure about Andrew Ng). Anyone who has worked in our field (AI, Machine Learning) can attest to that. AI is a complex and a rapidly evolving…


Added by ajit jaokar on August 7, 2018 at 6:32am — 3 Comments

Top 15 Scala Libraries for Data Science in 2018

In our previous articles, we have discussed the top Python libraries for data science. This time we will focus on Scala, which has recently become another prominent language for data scientists. It has gained popularity mostly due to the rise of Spark,…


Added by Igor Bobriakov on August 7, 2018 at 12:16am — No Comments

Leveraging Agent-based Models (ABM) and Digital Twins to Prevent Injuries

On the surface, preventing injuries to professional-caliber athletes would seem to have little in common with preventing operational failures for a machine (i.e., autonomous vehicle, locomotive, airplane, CT Scan).  However, both athletes and machines deal with inter-twined complex systems (where the interactions of one complex system can have a ripple effect on others) that can have significant impact on their operational effectiveness.

My son Max, the Director of…


Added by Bill Schmarzo on August 6, 2018 at 11:19am — No Comments

Building an expert system for NLP

Smart tags process: an algorithm for efficiently extracting useful information from a piece of text and storing it in a retrieval system.

The knowledge is extracted by asking the reader to answers a certain number of questions. Every time the answers to a question is yes, specifics tags are collected and stored. Every time the answer to a question is no, specific tags are also collected and stored. Some question ask the user to select in a list. In this case, all the elements…


Added by Issoufou Seidou Sanda on August 5, 2018 at 7:30am — No Comments

BI strategy beyond Excel

(This post originally appeared here

In a…


Added by Matthew Gierc on August 4, 2018 at 10:30am — No Comments

22 Differences Between Junior and Senior Data Scientists

What do experienced data scientists know that beginner data scientists don't know? Here is a quick overview.

  1. Automating tasks. Writing code that writes code.
  2. Outsourcing tasks to junior members or to consultants.
  3. Managing people, hiring the right people, managing managers who report to you.
  4. Training colleagues who might not be tech-savvy. Be an adviser for senior managers.
  5. Identifying the right tools and assessing the benefits and minuses of…

Added by Vincent Granville on August 4, 2018 at 8:00am — No Comments

Weekly Digest, August 6

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.

Featured Resources and Technical Contributions


Added by Vincent Granville on August 4, 2018 at 6:30am — No Comments

Open Peer-to-Peer Communications to Facilitate Real-time Insights Sharing

My blog “Blockchain + Analytics: Enabling Smart IOT” drew some great feedback asking me to clarify my autonomous vehicle example that used blockchain as a means of near real-time, peer-to-peer communications between clusters of intelligent devices and machines.  But first, some background.

Edge analytics within an Internet of Things (IOT) world is very…


Added by Bill Schmarzo on August 4, 2018 at 6:08am — No Comments

How to Get the Most Out of Your Predictive Analytics Tools [Infographic]

This content is no longer available. For similar infographics, see here.

Added by Olha Zhydik on August 3, 2018 at 4:00am — No Comments

Everipedia as a desk reference for data mining topics

One interesting metric to check the  usefulness of Everipedia as a desk reference for data mining is to compare the number of relevant articles. Go to Everipedia ( and search for "data mining". You will get 7 articles.Then go to Wikipedia and search "data mining" You will see 4 articles (overlapped with similar Everipedia  articles).

Another example. Try the word "smoothing" which is a popular topic in data analysis.…


Added by jwork.ORG on August 2, 2018 at 1:34pm — No Comments

Harnessing the power of data to transform asset-intensive value chains

In the twentieth century, oil was the most valuable resource – but not anymore. In today’s digital age data is the new oil. It will play a similar, perhaps bigger role, becoming a game changer that provides power in terms of information and competitive advantage through actionable insights. Some experts call it a commodity, but an ever-increasing one. The…


Added by Amit Supe on August 2, 2018 at 10:15am — No Comments

Thursday News: Apache Spark, ML with C++, Deep Learning, AI, R, Trend Analysis...

Here is our selection of featured articles, forum questions, and resources posted since Monday.



Added by Vincent Granville on August 2, 2018 at 9:00am — No Comments

Scalable IoT ML Platform with Apache Kafka + Deep Learning + MQTT

I built a scenario for a hybrid machine learning infrastructure leveraging Apache Kafka as scalable central nervous system. The public cloud is used for training analytic models at extreme scale (e.g. using TensorFlow and TPUs on Google Cloud Platform (GCP) via Google ML Engine. The predictions (i.e.…


Added by Kai Waehner on August 1, 2018 at 11:00pm — 1 Comment

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