Machine learning is one of the greatest technological advancements of the past decade. It allows programs and devices to recognize patterns in collected data and learn from it. Machine learning is already widely used, such as in recommendations on Netflix and Amazon based on viewing and purchasing history. The newest developments allow machine learning to recognize contexts and correlate patterns to situations. Machine learning can also be used to predict security breaches by detecting anomalies in malware data findings. It will be crucial for detecting new malware, with hundreds of thousands of new files arising daily. Machine learning has many potential future uses that are difficult to document fully.
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Machine Learning Advances in the 21st Century
1. i n t h e 2 1 s t c e n t u r y
M A C H I N E
L E A R N I N G
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2. One of the greatest and
most uncharted
technological
advancements in the past
decade has been the rise of
machine learning.
3. In a small scale sense, machine
learning is simply a program or device
that can recognize patterns and
messages from the data in which
they’re collecting and learn from it.
On the larger scale, machine learning
will take data collection and other
important functions that computers are
used for to the next level, and perhaps
one in which we need to manually
operate less and less.
4. According to tech data group SAS,
machine learning is everywhere
already. Recommendations prompted
by Netflix after you just watched your
favorite show or items you might be
interested in prompted by Amazon
after you’ve made a purchase are
actually some of the earliest forms of
machine learning in our technologically
advanced world.
5. Some of the newest advancements in
machine learning are coming in the
forms of recognizing context. This is a
step up from simply recognizing
patterns; this is taking patterns and
recognizing how they could correlate
to a situation. Businesses around the
world have even begun using this in
their customer service practices.
6. Forbes recently published an article
discussing how security will play an impact
with machine learning and pointed out a
few interesting points about security as it’s
protected now. From their findings, almost
all malware codes used now to protect
data are only about 2-10% different from
the version it previously upgraded from.
7. With newer machine learning, anomalies in
malware data findings can be reported in
order to predict security breaches and not
just when one happens. With so much to
detect – hundreds of thousands of new
malware files arise every day – machine
learning will be crucial.
8. Machine learning is going to be used in so
many unique forms that it’s difficult to
write about all of the exciting new uses
without writing a book! Over the next few
months, stay tuned to my blog to see my
take on new advancements in technology,
wins and losses in the machine learning
community, and what all of this means for
our daily lives.
9. f o r m o r e p l e a s e v i s i t :
T H A N K S F O R
R E A D I N G !
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