✎ Issue #3 - A.I. Marketing, What's an Algorithm & Show Me The Data

We focus on Ai business related topics that you need to know, can use and get started with now.  Ei

Everyman's Ai & Blockchain ✎ Digest

September 12 · Issue #3 · View online
➥ Your "Low-tech" Artificial Intelligence & Blockchain insights into practical and fast-track A.I. ideas to grow your business today!

We focus on Ai business related topics that you need to know, can use and get started with now.  Einstein’s KISS explained simply:

“If you can’t explain it simply, you don’t understand it well enough.” 
              - Albert Einstein

1) A.I. Ready Solutions: Marketing & Brand Building
Out-of-the-box A.I. enabled marketing solutions is a saturated market. I currently track and profile 128 best-in-class such companies.  “The hype machine is in full swing” per the first article below.  Yet, same says “AI will undeniably be the intelligence backbone of likely all technology systems at some future time”.  Examples of A.I. ready marketing & sales solutions:
➧ Churn prediction & smart customer engagement 
➧ AI-powered content creation
➧ AI-enhanced PPC advertising & Ad targeting
➧ AI-powered customer insights
➧ Predictive customer service

Below are 5 low-tech articles worth scanning.  Sales & marketing A.I. automation is a favorite topic of mine and will explore more in upcoming issues. Ask Me a Question: CLICK HERE
➥ Artificial Intelligence is Here: 5 Brands Using AI
2) A.I. Demystified: "Algorithms"
➥ What is an algorithm and why should you care?
Algorithm Definition: A step-by-step procedure for solving a problem or accomplishing some end especially by a computer.  

An Algorithm But Not Machine Learning: Given a list of positive numbers, return the largest number on the list.  Pretty straightforward procedure for solving for maximum.  Is the 1st # larger than the 2nd, if yes, discard #2 and, repeat.

Simplest Machine Learning (ML) Algorithm:
Given the 4 data points in the below chart, find the best-fitting straight line through the points so that the line minimized the distance all the points are from the line.  The algorithm to solve this is called “linear regression” and the technical term that qualifies this as a machine learning algorithm is “optimizing a loss function”.  Once the computer has learned the best fitting line based on a training data set, you can then predict Y given a new X value.  For example, X is square feet of a house, Y is the price.  ML algorithms get much more complex and there is a debate whether linear regression is really a ML algorithm or just statistics.  The answer is, yes, according to this article Click Here.   At any rate, all machine learning algorithms, simple or complex, need good data, lots of it, to be trained. Read next section “Show me the data!”.
3) Show Me The Data!
➥ Why “Big Data” Is a Big Deal
About Author | everymans.ai
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