Two New Deep Conjectures in Probabilistic Number Theory
The material discussed here is also of interest to machine learning, AI, big data, and data science practitioners, as much of the work is based on heavy data processing, ...
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Data Scientist, Business & IT – Importance to have everyone on the same page, key challenges and recommendations
Data science has become an integral part of a 21st century organization. Almost all the companies, large, medium or small, want to utilize data science to fulfill their b...
Comparing Model Evaluation Techniques
In my previous posts, I compared model evaluation techniques using Statistical Tools & Tests and commonly used Classification and Clustering evaluation techniques In ...
Can Data Analytics Really Deliver 1300% ROI?
With the right business problem, data, and applied techniques predictive analytics can deliver exceptional return on investment (ROI) by, for example, assessing and manag...
Using Python and R to Load Relational Database Tables, Part II
Last time I wrote on using Python/Pandas as an adjunct to loading PostgreSQL tables. In this sequel, I demo how R can be used to collaborate with the database in a simi...
Enter the Era of Terabyte Memory
Enabling cost-effective terabyte main memory along with third-party observations of a “profound” change in storage, Intel® Optane™ DC persistent memory modules cha...
Where’s the Love – Trends in Data Science Career Opportunities
Summary: The annual Burtch Works salary survey tells us a lot about which industries are using the most data scientists and the difference between higher and lower ski...
State of #AI 2019 Report
I highly recommend the #StateofAI 2019 report. I have followed this report from By Nathan Benaich and Ian Hogarth The report is free and you can download it at stateo...
Privacy and AI – How Much Should We Really Care
Summary: More data means better models but we may be crossing over a line into what the public can tolerate, both in the types of data collected and our use of it. Th...
DSC Webinar Series: Why Data Prep is Step 1 for Analytics Success
Sad but true when it comes to data prep – data practitioners spend up to 80% of their time scrubbing and preparing their data before performing any meaningful analy...