*What is Machine Learning? -Definition -Explanation *Difference between Machine Learning and Standard Programs *Machine Learning Models -Supervised Learning --Classification --Regression -Unsupervised Learning --Clustering *AI Evolution -History of AI -Neural Networks and Deep Learning -Simple Neural Network and Deep Neural Network -Difference between AI, Machine Learning, and Deep Learning

1. Mostafa Elsheikh
AIET - Computer Engineering
October, 2017
Supervised by Dr. Walid M. Saad
Intro to Machine Learning & AI

2.  AI Evolution
 History of AI
 Neural Networks and Deep Learning
 Simple Neural Network and Deep Neural
Network
 Difference between AI, Machine Learning,
and Deep Learning
 What is Machine Learning?
 Definition
 Explanation
 Difference between Machine
Learning and Standard
Programs
 Machine Learning Models
 Supervised Learning
 Classification
 Regression
 Unsupervised Learning
 Clustering
Overview
MostafaElsheikh
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3.  The field of study that gives computers the ability to learn
without being explicitly programmed.
 Is a method of teaching computers to make predictions
based on some data.
 It is a branch of Artificial Intelligence which automatically
improves programs using data.
What is Machine Learning?
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4. A machine learning system could be trained on email messages to learn to
distinguish between spam and non-spam messages.
After learning, It can be used to classify new email
messages into spam and non-spam folders.
What is Machine Learning?
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5.  In machine learning, you feed the computer the following things:-
 Input (experience)
 Output (output corresponding to inputs)
 And get the model/program as output. With the help of this program, you can perform some tasks.
 On the other hand, in a standard program, you feed the computer the following things:
 Input
 Program (how to process the input)
 And after that you get the output.
How Machine Learning Differs From Standard Programs
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6.  Data is grouped into
known categories
 Algorithm learns which
group outcomes belong
to
Ex. Email spam classification
Classification
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7.  Best fit analysis used to
determine likely
outcome
Ex. House prices prediction
Regression
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8.  The organization of
unlabeled data into
similar groups called
clusters.
 A cluster is a collection
of data items which are
“similar” between them,
and “dissimilar” to data
items in other clusters.
Unsupervised Learning - Clustering
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9.  The organization of
unlabeled data into
similar groups called
clusters.
 A cluster is a collection
of data items which are
“similar” between them,
and “dissimilar” to data
items in other clusters.
Ex. News clustering
Unsupervised Learning - Clustering
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10.  History of AI
Computers Playing Games
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11.  Mimics Human Brain
 Series of ML Nodes
 Improvement in
Predictive Ability
Neural Networks – Deep Learning
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12.  Mimics Human Brain
 Series of ML Nodes
 Improvement in
Predictive Ability
Neural Networks – Deep Learning
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13.  Mimics Human Brain
 Series of ML Nodes
 Improvement in
Predictive Ability
Neural Networks – Deep Learning
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14. Any Questions?
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