Course Name: Get Started in Machine Learning with Python scikit-learn. Learn the science of discovering patterns and making intelligent predictions from big data. 5 day bootcamp designed to help you learn basic principles needed to understand and apply Machine Learning models and methods using Python Scikit-Learn. For corporate bookings or to organize on-site training email hello@persontyle.comor call now +44 (0)20 3239 3141 www.persontyle.com

1. © 2014 Persontyle Ltd. All rights reserved.
GET STARTED IN
MACHINE LEARNING
WITH PYTHON SCIKIT-LEARN
5 DAY BOOTCAMP
21-25 JULY 2014, LONDON

2. Data generated through our activities captures plethora of
information about our identity, likes and dislikes etc. This
information has tremendous value in every aspect of human life.
Programming computers to unravel this hidden information is
what Machine Learning is all about. It is the art and science of
scientifically deriving insights, patterns and predictions from data.
www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
<MACHINE LEARNING>
“The field of machine learning is concerned with the
question of how to construct computer programs
that automatically improve with experience.”
- Tom Mitchell
Machine Learning models and programs automatically make
decisions from data in order to achieve some goal or requirement.
Machine learning models matter to the world. Because they are;
#EFFICIENT
Machine Learning models predict and detect partners faster than any other
manual program or method.
#EFFECTIVE
Machine Learning models can do better job than humans when analysing and
predicting large scale and streaming data sets (big data).
#SCALE
Machine Learning models can provide solutions to large data problems that
traditional systems can not solve.
LEARN THE SCIENCE OF DISCOVERING PATTERNS AND MAKING
INTELLIGENT PREDICTIONS FROM BIG DATA

3. www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
 Machine perception
 Computer vision, including object
recognition
 Natural language processing
 Pattern recognition
 Search engines
 Medical diagnosis
 Bioinformatics
 Brain-machine interfaces
 Detecting credit card fraud
 Stock market analysis
 Classifying DNA sequences
 Sentiment analysis
 Affective computing
 Information retrieval
 Recommender systems
MACHINE LEARNING CAN APPEAR IN MANY GUISES
Examples in the real world include handwritten recognition, weather
prediction, fraud detection, search, facial recognition, and so forth are
all examples of machine learning in the wild. Applications for Machine
Learning include:
“Over the past two decades Machine Learning has become one of the
mainstays of information technology and with that, a rather central,
albeit usually hidden, part of our life. With the ever increasing amounts
of data becoming available there is good reason to believe that smart
data analysis will become even more pervasive as a necessary
ingredient for technological progress.”
DR. ALEXANDER J. SMOLA, PROFESSOR, CARNEGIE MELLON UNIVERSITY

4. Why write programs when the computer can instead learn them from data? In
this 5 day bootcamp you will learn how to make this happen. Though it has
been an area of active research for over 50 years, Machine Learning is
currently undergoing a renaissance driven by Moore's law and the rise of big
data. Large private and public investment in the area has given us self driving
cars, practical speech recognition, effective web search, and a vastly improved
understanding of the human genome. Computer based machine learning
algorithms now outperform humans on tasks such as handwritten digit
recognition, traffic sign recognition, and even on some complex reasoning
tasks as demonstrated by IBM's Watson winning Jeopardy.
Bootcamp is designed to help you learn basic principles needed to understand
and apply Machine Learning models and methods using Python Scikit-Learn.
Lots of hands-on examples to step through real-world application of Machine
Learning. Attending this bootcamp will enable you to understand the basic
concepts, become confident in applying the tools and techniques, and provide
a firm foundation from which to explore more advanced methods.
www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
[5 day bootcamp to learn basic building blocks of practical Machine Learning]
GET STARTED IN MACHINE LEARNING
WITH PYTHON SCIKIT-LEARN
“In a way Machine Learning has become the new black gold. The
application areas are literally endless and from where we stand we
haven't even reached the inflection point. If you think about it, there
are many industries out there that are just waking up to the reality of
big data and data science.”
MARTIN HACK, CEO SKYTREE
Python and scikit-learn logos are the property of their respective owners

5. WHAT WILL YOU LEARN?
Attend the bootcamp to learn the basic concepts, models and
techniques required to perform practical Machine Learning.
GET STARTED IN
MACHINE LEARNING
www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
DAY 1
Understand how the structure and function of the human brain is different from a
computer and how this affects learning in each.
Define Machine Learning, why it matters, and discuss its relationship to data mining,
data science, and statistics.
Understand the steps in the machine learning pipeline, from data acquisition and
feature generation, to training and model selection.
Overview of core Machine Learning terminology i.e. features, instance, model
selection, bias, variance, generalization, precision, etc.
Review of the fundamentals of linear algebra, calculus, statistics, and probability
theory.
DAY 2
Doing Machine Learning - Review fundamentals of practical Machine Learning
• Reading the data and cleaning it.
• Exploring and understanding the input data.
• Analysing how best to present the data to the learning algorithm.
• Choosing the right model and learning algorithm.
• Measuring the performance correctly.
Basics of Python programming language and environment.
Scientific Python building blocks and workflow
• NumPy: Base n-dimensional array package
• SciPy: Fundamental library for scientific computing
• IPython: Enhanced interactive console
• Pandas: Data structures and analysis
Overview of Scikit-learn: Machine Learning in Python
Our first Machine Learning Application - K Nearest Neighbours
Labs
• Setting up the environment
• Python programing basics (load data, simple histogram, select rows, columns,
scatter plot, simple stats, ...)
• Linear Regression

6. WHAT WILL YOU LEARN?
GET STARTED IN
MACHINE LEARNING
www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
DAY 3
Generally Applied Algorithms and Applications
• Naive Bayes
• Support Vector Machines
• Logistic Regression
• Decision Trees
Labs
• Detecting Spam using Machine Learning
• Predicting house prices with regression
• Image recognition with Support Vector Machines
DAY 4
Dimensionality Reduction - Reducing the number of random variables to consider
• Feature selection and feature extraction methods
• Principal Component Analysis
Clustering - Automatic grouping of similar objects into sets.
• Overview of clustering methods
• Applications and Algorithms
Basics of Crab - Recommender systems in Python
BigML - Putting the power of Machine Learning in your hands
Labs
• Dimensionality reduction practical example
• Clustering handwritten digits with k-means
Python and scikit-learn logos are the property of their respective owners.

7. WHAT WILL YOU LEARN?
GET STARTED IN
MACHINE LEARNING
www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
DAY 5
Model Selection and Evaluation in Scikit-learn - Comparing, validating and choosing
parameters and models
Overview of Pre-processing in Scikit-learn - Feature extraction and normalization.
Putting it all together - Final Kaggle Project
Current Hot Topics
• Large scale Machine Learning
• Deep Learning
• Watson style learning
• Probabilistic programming
• Machine Learning as a Service
WHO SHOULD TAKE THIS COURSE?
You are interested in Machine Learning. You have read a book or
taken an online course and now want to know more and learn how to
apply Machine Learning to solve real problems. Well-suited to
machine learning beginners or those with some experience.
All Machine
Learning
Enthusiasts
Business
Professionals
Technologists/
Developers
Data/Market/
Research
Analysts
Business/
Technology
Consultants
PREREQUISITES
Basic understanding of calculus, statistics, probability theory,
linear algebra. This will be refreshed but not in detail. Basic
knowledge of python is required. All lab sessions will be done using
IPython notebooks and Scikit-learn.

8. Persontyle trainers are passionate about meeting each participants
learning needs. They have been chosen both for their extensive
practical Data Science and Machine Learning experience and for
their ability to educate and interact with natural empathy. All of our
trainers have worked on a variety of data science and Machine
Learning projects. They share their academic knowledge and real-
world experience and each individual adds their own unique
perspective to the course. Our trainers present in a style that is
informal, entertaining and highly interactive.
Guest Speakers
Business leaders, Machine Learning practitioners, and academic
researchers covering use cases, case studies and sharing practical
experience of applying Data Science and Machine Learning in their
organizations.
COURSE INSTRUCTORS
“A breakthrough in Machine Learning
would be worth ten Microsofts”
BILL GATES, CHAIRMAN, MICROSOFT
www.persontyle.com© 2014 Persontyle Ltd. All rights reserved.
GET STARTED IN
MACHINE LEARNING
WHAT SHOULD I BRING?
Along with bringing your laptop and charger, don’t forget to bring
loads of curiosity, scepticism, eagerness to participate and the
desire to learn.

9. THE SCHOOL OF DATA SCIENCE
The School of Data Science, a project of Persontyle, specializes in designing and delivering
structured, relevant, practical and affordable learning experiences for all of us to
understand data science in simple human terms.
RETURN ON INVESTMENT (ROI)
CONVINCE YOUR BOSS
We all need to learn how to analyse data, find the value and glean
insights. The advent of the data driven connected era means that
analyzing massive scale, messy, noisy, and unstructured data is going
to increasingly form part of everyone's work.
The School of Data Science learning programs provide a unique
investment opportunity that pays for itself many times over.
For corporate bookings or to organize on-site training email
hello@persontyle.com or call now +44 (0)20 3239 3141
www.persontyle.com/school
World-class
Instructors
Develop Practical
Data Science Skills
Real World
Industry Use Cases
Short Courses For
Time Convenience
Value For
Money
Register Now
Limited seats. We encourage you to register as soon as you can.
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"For the best return on your money, pour your purse
into your head."
- Benjamin Franklin