This document discusses how machines can make decisions using machine learning approaches. It provides an overview of machine learning vocabulary and techniques including supervised learning methods like regression and classification. It also discusses unsupervised learning and examples of clustering emails. The document then demonstrates simple linear and logistic regression models to predict outputs given inputs. It discusses evaluating models through error measurement and mentions several other machine learning techniques. Finally, it provides an overview of neural networks including feedforward networks and different types like convolutional and recurrent neural networks.
3. Agenda
• Introduction
• Machine Learning Vocabulary
• Machine Learning approaches
• Other ML Techniques
• Introduction to Neural Networks
• Different types of Neural Networks
• GPGPU : General-Purpose Computation on GPU
• Other AI Components: Within an Enterprise
• Q&A
4. A forgotten definition of Computer
“Computer is an electronic device that process information as per predefined
instruction/rules”
5. A forgotten definition of Computer
“Computer is an electronic device that process information as per predefined
instruction/rules”
and with Artificial Intelligence
“Computers can also look at past instances of an event, look at the
inputs and outputs, and then predict the outputs for given inputs
without pre-defined instructions/rules”
6. Why Artificial Intelligence
is so relevant now?
• Large scale Storage and
Faster Compute (but
smaller in size) are possible, all
available over Cloud*
* Digital Evolution Revolution
8. An approach to Machine Learning - Human
Intelligence
• How do we make decisions while driving the car?
• How does an experienced stock trader places his order?
• How do a doctor diagnosis your illness?
Explicitly or Implicitly human beings learn to read (and understand
the impact) of the parameters
10. Types of Machine Learning
Machine
Learning
Supervised:
Supervised learning is
the machine learning
task of inferring a
function from labeled
training data.
Regression: Outcome
is continuous
(numerical)
Classification:
Outcome is a
category
Unsupervised:
Unsupervised learning is
a type of
machine learning
algorithm used to draw
inferences from datasets
consisting of input data
without labeled
responses.
Ex: Categorizing the emails to Primary, Social,
Promotions, Updates, Forums
Ex: Predicting Stock price
Ex: Explore the set a given data set and identify
possible classifications within the data
18. Life is not always simple equations
• Linear Regression
• Logistic Regression
• Polynomial Regression
• Stepwise Regression
• Ridge Regression
• Lasso Regression
• ElasticNet Regression
Applying mathematical/statistical approaches for finding the relationship
between inputs and outputs (Historical events)
19. Not just all .. there are other techniques as well
Support Vector Machine / Support Vector Classifier
Kernel Approximation : An approach of applying a simplification function over any input (A simple Definition)
Principal component analysis: An approach to take only the relevant features, or identify the relevant features
….
21. It’s the system that
matters
If the bee disappeared off the surface of the globe,
then man would have only four years of life left. No
more bees, no more pollination, no more plants, no
more animals, no more man.
-- Albert Einstein
A closer look at another Machine
learning approach inspired from
this MACRO/MICRO universe
31. Different types of Neural Networks
• Convolutional Neural Networks :A Convolutional neural network
(CNN, or ConvNet) is a class of deep, feed-forward artificial neural
networks that has successfully been applied to analyzing visual
imagery.
• Recurrent Neural Network(RNN): Hidden layers receive their own
outputs as input
• Long / short term memory (LSTM): An improvement over RNN
• Restricted Boltzmann machines (RBM),Deep Belief Networks (DBN) ,
Deep convolutional inverse graphics networks (DCIGN)….
*http://www.asimovinstitute.org/neural-network-zoo/
by Fjodor Van Veen
32. GPGPU : General-Purpose Computation on GPU
* Images are copyright material of subsequent brands