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 Machine learning is a branch of artificial intelligence (AI) that allows
computers to learn and develop on their own without having to be
directly programmed. Machine learning is concerned with the
development of computer programmes that can access data and
learn on their own.
 Some of the examples are
Image Recognition. Image recognition is one of the most common
uses of machine learning.
Speech Recognition. Speech recognition is the translation of spoken
words into the text.
 Supervised Learning
Supervised learning describes a class of problem
that involves using a model to learn a mapping
between input examples and the target variable.
Applications in which the training data comprises
examples of the input vectors along with their
corresponding target vectors are known as
supervised learning problems.
 Unsupervised learning
It describes a class of problems that involves using a model to
describe or extract relationships in data.
Compared to supervised learning, unsupervised learning operates
upon only the input data without outputs or target variables. As
such, unsupervised learning does not have a teacher correcting the
model, as in the case of supervised learning.
In unsupervised learning, there is no instructor or teacher, and the
algorithm must learn to make sense of the data without this guide.
 Reinforcement Learning
Reinforcement learning describes a class of problems where an
agent operates in an environment and must learn to operate using
feedback.
Reinforcement learning is learning what to do — how to map
situations to actions—so as to maximize a numerical reward signal.
The learner is not told which actions to take, but instead must
discover which actions yield the most reward by trying them.
 LearnBay is a Bangalore based
Data Science Institute which is
dedicated to help students ,
professionals to become Industry –
ready in Data Science. LearnBay
provides IBM Certificates in Data
Science.
 Our Key features are :
 200 + Hours of classroom sessions
 Live classes with recording of all
the classes
 Flexibility in Scheduling classes
 Class strength not more than 10
 Highly qualified trainers
 12+ Real time project and case
studies
 Job Assistance – Resume building,
mock interview and job referrals
 Address : Learnbay,19/1,2nd Floor, Classic
Aura(Beside Aricent),Marathahalli -
Outer Ring Road,Kadubeesanahalli,
Bengaluru, Karnataka
 Email : contact@learnbay.in
 Cell No :+918861279311

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Machine Learning Types & Data Science Training

  • 1.
  • 2.  Machine learning is a branch of artificial intelligence (AI) that allows computers to learn and develop on their own without having to be directly programmed. Machine learning is concerned with the development of computer programmes that can access data and learn on their own.  Some of the examples are Image Recognition. Image recognition is one of the most common uses of machine learning. Speech Recognition. Speech recognition is the translation of spoken words into the text.
  • 3.  Supervised Learning Supervised learning describes a class of problem that involves using a model to learn a mapping between input examples and the target variable. Applications in which the training data comprises examples of the input vectors along with their corresponding target vectors are known as supervised learning problems.
  • 4.  Unsupervised learning It describes a class of problems that involves using a model to describe or extract relationships in data. Compared to supervised learning, unsupervised learning operates upon only the input data without outputs or target variables. As such, unsupervised learning does not have a teacher correcting the model, as in the case of supervised learning. In unsupervised learning, there is no instructor or teacher, and the algorithm must learn to make sense of the data without this guide.  Reinforcement Learning Reinforcement learning describes a class of problems where an agent operates in an environment and must learn to operate using feedback. Reinforcement learning is learning what to do — how to map situations to actions—so as to maximize a numerical reward signal. The learner is not told which actions to take, but instead must discover which actions yield the most reward by trying them.
  • 5.  LearnBay is a Bangalore based Data Science Institute which is dedicated to help students , professionals to become Industry – ready in Data Science. LearnBay provides IBM Certificates in Data Science.  Our Key features are :  200 + Hours of classroom sessions  Live classes with recording of all the classes  Flexibility in Scheduling classes  Class strength not more than 10  Highly qualified trainers  12+ Real time project and case studies  Job Assistance – Resume building, mock interview and job referrals
  • 6.  Address : Learnbay,19/1,2nd Floor, Classic Aura(Beside Aricent),Marathahalli - Outer Ring Road,Kadubeesanahalli, Bengaluru, Karnataka  Email : contact@learnbay.in  Cell No :+918861279311