Machine Learning Courses
INTRODUCTION
Machine
Learning- a branch of artificial intelligence and as the name would suggest,
the process of teaching machines how to learn. You heard that! It is the
mechanism by which we make computers and systems capable of taking decisions on
their own using data as their basis of input. Computers use raw data, data science course syllabus process
them using advanced algorithms, and accordingly learn, understand, and tune
their performance to the desired levels of accuracy, so that a similar kind of
decision can be taken in the future without any human intervention. Using the
concepts and basics of big data and data analytics, machine learning has
enabled automation of a lot of the core tasks in a wide variety of industries.
With an
estimated 5 billion gigabytes of data (~5000 petabytes ~5 exabytes) generated
by the world on a daily basis has made it impossible to process and filter such
colossal amounts of data. At least the thought of humans doing it is completely
out of the scope. But with computers and systems having evolved into machines
with monstrous processing capabilities, machine learning proves to be a life
savior in conducting data analytics and also facilitate in making better,
enhanced and informed decisions. The best part about machine learning is that
it holds true for the saying- “The more the merrier”. The fact that more is the
data supplied to the model better is the efficiency and precision of the
output. As such, the vast amount of data that is generated on a daily basis is
put to quality use instead of just getting wasted and discarded.
CHALLENGES
With a countless
number of advantages to the study of machine learning, let us take a look at
the other side of the coin.
●
DATA
SIZE: Even after so many
advancements in the computing power of machines, there are limitations to them
also. Even the biggest of companies and businesses having large infrastructure
and supercomputers at their disposal can only process close to 1-2% of the data
that is generated every day; that is almost 50 petabytes of data can be
processed in a single go. Even after being a ridiculous amount of data that is
getting processed, the amount that is wasted is exponentially more. Even after
using concepts of parallel and distributed programming can this figure be taken
to a maximum of 5-6% only.
●
VARIETY: One of the many aspects of big data is its
variety which is a major cause of the generation of heterogeneous aspects of
output which make absolutely no sense when compared with the problem and its
expected solution. Therefore the challenge of segregating and filtering the
unnecessary aspects of data before it can be sent for processing is a major
headache.
●
DATA
VERACITY: The reliability of
the data source and the accuracy of the data science courses in hyderabad play a pivotal part in generating
outputs that are neutral and confer to the target audience in a neutral
fashion. Discrepancies, abnormalities, redundancies, duplications, biases etc.
are some of the aspects that should be kept in mind and eradicated completely
in order to enhance the overall accuracy of the data and consequently the
overall precision and also stick to the associativity and interrelations.
RESOURCE BOX
Being one of the hottest and the most in-demand industry of the
present day world in terms of requirement of skilled people, the fields of data
science and machine learning are one to ponder your future over. Join datascience courses in by 360DigiTMG: one of the best places to get certified in
Bangalore.
Contact:-
2-56/2/19,
3rd floor, Vijaya towers near Meridian school, Ayyappa Society Rd, Madhapur,
Hyderabad, Telangana 500081
9989994319
For more info Click here
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