This workshop covers parts of data science - Analytics, Machine Learning and an intro to Deep Learning with some use cases in the cyber security space.

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Thinking Beyond the
Human Envelope
A Quick Workshop on Data Science using Machine Learning
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Shomiron DAS GUPTA - Founder, CEO
NETMONASTERY Inc.

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Agenda
■ More on Analytics, ML and DL
■ Why Analytics today?
■ Where does Analytics take us
■ Machine Learning, Simply
■ The Royal Family of ML
■ Solving with ML
■ Deep Learning - Where to NEXT !
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Building Context Grounds Up

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More on Analytics, ML and DL
Data Science has many children -
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Let’s Get it Straight - Data Science is Big
Data Analytics Machine Learning Deep Learning

4. Data Analytics
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Why Analytics Today?
We created 90% of the world's data in the last 2 years
Largest customer in 2014 was generating 4TB / Month,
the same customer today is generating 69TB / Month
Need to look through and analyze the recorded past - there is a clear want to
reference and learn from our data, more so in the cyber security
Horizontal scaling is the key - brings speed with consistency
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Bringing History Back into Cyber Security

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Where Does Analytics Take Us?
What Works Well with Big Data Analytics Engines
Thresholding / Multi-Dimensional Thresholding
Time Series Analytics including Heuristics
Baseline / Profilers
Correlators
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Different Forks Available to Process Big Data
Wheels on Fire

7. Machine Learning
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Machine Learning, Simply
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It’s the ability to make machines think and take experiential decisions,
it’s the ability of the machine to think beyond the human envelope.
Speed / Accuracy of decision making
Ability to perform “logically” in unknown conditions
Let’s Try to Define Machine Learning

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Reinforced Learning
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The Royal Family of ML
First - Classification and Regression
■ Trees - Decision Trees
■ Forests - Random Forests
■ Support Vector Machines
■ K Nearest Neighbours (KNN)
■ Linear / Logistic Regression
■ Neural Networks
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Describing the Tip of the Iceberg

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How it Works - Simple Decision Tree
The Basics
Features
Labels
Dataset
Training
Testing
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Consistent Decision Making - is something we could all use ;)
The Process
Selecting the right features
Moderating and cleaning the dataset
Splitting the dataset - train / test
Building and training a model
Testing for accuracy - chaining / pipelining etc.

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Solving with ML
■ Email SPAM !
■ Detecting / Generating DGN’s
■ Network Anomaly
Stuff we (DNIF) does
■ Detect InBots
■ Bad traffic to Applications
■ UBM - Bad Access Attempt
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Cyber Security Challenges that have their roots in ML

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Deep Learning - Where to NEXT !
Google with Deep Learning
■ Voice API
■ Video API
■ Image API
■ Translation API
■ Speech API
■ Relearning
■ finally TensorFlow
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What is currently available - Where are we trying to go...

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Where to Begin
1. Massive resources on YouTube
2. Best if you learn - Python / R ….. python will take you the farthest
3. Work on practical challenges - seek answers
4. Big data platforms with built-in logic
Splunk.com - Leader in Big Data Analytics
DNIF.it - Complete toolkit. 100G Free Forever
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NO, YOU ARE NOT LATE !

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Thank You
email: shom@dnif.it
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