Artificial intelligence isn’t the future — it is the present. Already, businesses are deploying AI tools in a variety of ways: improving marketing and sales, guiding research and development, streamlining IT, automating HR and more.  https://www.tycoonstory.com/technology/deep-learning-vs-machine-learning-what-business-leaders-need-to-know/

1. Deep Learning vs. Machine Learning:
What Business Leaders Need to Know
Artificial intelligence isn’t the future — it is the present. Already, businesses
are deploying AI tools in a variety of ways: improving marketing and sales,
guiding research and development, streamlining IT, automating HR and more.
The morebusinessleaders can learn aboutAI and how to leverage it, the better.
Yet, plenty of business leaders remain a bit baffled by the jargon of AI —
particularly when it comes to machine learning. Machine learning is a branch of
artificial intelligence tech wherein machines are given algorithms that allow
them to learn fromdata and improvetheir processes. While someuse machine
learning and artificial intelligence interchangeably, the truth is that the former
is a specific field within the latter.
Even more confusing, there is another term, “deep learning.” Is this merely a
different way of saying “machine learning,” or is this yet another field of AI?
Read on to find out.
First, a Deeper Dive Into Machine Learning
As mentioned above, machine learning is a branch of artificial intelligence that
relies on algorithms to identify patterns from data and apply lessons from those
patterns to future decisions. Machine learning is the source of a vast array of
automated tasks across various industries. A common example of machine
learning is an on-demandvideo streamingservicethat trackswhichvideosa user
watches and recommends similar videos by learning the viewing history of
similar users. Business leaders in different industries can take machine learning

2. shortcourses onlineto learn moreabouthow to apply machine learning tech to
improve processes within their organization.
In truth, machine learning is essentially a mechanical function, not unlike a
flashlight or a phone screen. Machine learning programs cannot deviate from
the directions given to them by their algorithms; they collect a certain type of
data, analyze it in a certain type of way and refine their processes in a certain
manner before starting the sequence over again. This is in contrastto artificial
intelligence, which aims to simulate human behavior outside of explicit
programming.
This isn’t to say that machine learning isn’t complex. In fact, machine learning
has the capacity to be superior to human learning as determined by the
algorithms used to direct machine learning functions.
Deep Learning Is a Type of Machine Learning
A subfield of machinelearning, deep learning useslayersof algorithmsthat form
artificial neural networks capable of recognizing errors in its own analyses. In
basic machine learning, programs requirehuman intervention if predictions are
inaccurate; in deep learning, the complex neural network provides checks and
balances on the system, guiding it toward greater and greater accuracy without
the need for human correction.
Artificial neuralnetworksmimic the processesusedin thehuman brain. A model
of brain cell interaction first developed in 1949 describes how neurons grow
together when consistently used, which is what results in accrued knowledge.
Deep learning integrates nodes,which increaseordecreasein relative weight as
the programgains more information about a specific topic. However, because
deep learning applications can process much more data at a much faster pace,
programs can identify much more complex connections than the human brain.
Thus, deep learning tools are exceedingly valuable.
However, deep learning is not without flaws. Just as different people can draw
different conclusions from the same set of data — as exemplified by lateral
thinking puzzles —deep learning programs can cometo the wrong conclusions.
To ensure accurate results, artificial neural networks require intense training,
which involves tinkering with the mathematical functions guiding its algorithms
to ensure that the right nodes have the right weights. Not everyone has the

3. capacity to train a deep learning toolcorrectly; itis a taskbestreservedfor those
well-educated and experienced in the machine learning field.
AI isn’tjustoneconcept — it is a vastfield of technologies and ideas. Already, AI
and machine learning tools are essential for certain business functions; soon, it
is possiblethatbusinessesunableor unwilling to dabblein deep learning will get
left in the dust. The sooner business leaders understand how to leverage the
different types of machine learning, the surer their place in the future of
industry.