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3 Goals of Machine Learning (via

machine learning, ai, algorithms

Definition of Machine Learning

Machine learning, what is it?  Basically it is learning to do better in the future from what has been done in the past.  This is done through algorithms that make the computer learn to complete actions through automatic means.  In other words, the computer learns to do stuff on its own, not through getting help from people.  It’s a part of artificial intelligence, a sub-menu.

Examples of Machine Learning

  • Optical character recognition
  • Face detection
  • Spam filtering
  • Finding topics
  • Understanding spoken languages
  • Medical diagnosis
  • Customer segmentation
  • Detecting fraud
  • Predicting weather

Goals of Machine Learning

  1. Make general purpose algorithms
  2. Learning algorithms
  3. Find prediction rules easy for people to understand

Very interesting article on learning more about machine learning.


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Risky AI business: Navigating regulatory and legal dangers to come (via CIO)

ai, machine learning, business

AI Intro

Artificial intelligence poses a range of hidden and unknown dangers for enterprises deploying the technology. Here’s how to guard against the legal and compliance risks of AI.

Source: CIO

Now who would have expected this?  I sure didn’t.  It’s a wake up call when you have to consider regulations and possible legal ramifications of using AI in certain industries.  “Context, ethics, and data quality are issues that affect the value and reliability of AI, particularly in highly regulated industries,” says Dan Farris, co-chairman of the technology practice at law firm Fox Rothschild, and a former software engineer who focuses his legal practice on technology, privacy, data security, and infrastructure matters. “Deploying AI in any highly regulated industry may create regulatory compliance problems.”  Source: CIO

Best Practices

  • Have a thorough grasp of how the machine makes its decisions
  • Design systems to gather reasonings of decisions made
  • Make sure you’re in regulations
  • Develop industry specific rules
  • Knowing when it is safer to use Artificial Intelligence to human brain power

Very interesting information.


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Article: Evolutionary algorithms are the living, breathing AI of the future

Evolutionary algorithms are the living, breathing AI of the future

This is so interesting and exciting! Think of everything that can and will be able to be done in the future. It’s open wide with almost no barriers. Can’t wait to see what the future brings.

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Machine Learning and Artificial Intelligence Trends in 2018 – DATAVERSITY (via DATAVERSITY)

machine learning, ai, artificial intelligence, big data

AI and Machine Learning

Predictions put Artificial Intelligence (AI) and Machine Learning as becoming the game-changers of the coming decade.


This is so interesting!  Consider what will happen in the next few years with all the new technologies being created and built now.  Think about what AI and machine learning will do for us, situations where it can help and how it helps now.

There is so much going on to consider in every industry.  So many ideas of how to improve what is already in the office, like building robotic assistants and self-teaching algorithms for handling the new Intelligence Analytics systems.  Think of what the creating and building that will happen because of this.  So exciting and a lot to think about isn’t it?

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What is ERP? A guide to enterprise resource planning systems (via CIO)

ERP, upgrade system, business, strategy

A very interesting and in-depth article about ERP and why you should consider using it.  A very good read that gives a lot of good information.

The Article

ERP combines software systems from departments like finance, human resources and warehouse management.  It combines it into a single, integrated software program running off a single database.  This way the various departments can more easily share information and collaborate. It’s a tall order, but that integrated approach can have a tremendous payback if companies install the software correctly.

Source: CIO