This document provides an introduction to a course on machine learning. It discusses the large amounts of data now available due to factors like the internet and big data. It also introduces programming and machine learning concepts like data types, variables, conditionals, loops, functions, and classes. Python is presented as a useful programming language for machine learning, with examples of code shown. Setting up an environment with Anaconda and Jupyter Notebook is also covered to allow hands-on coding practice.

1. Introduction to
Machine Learning
(5 ECTS)
Giovanni Di Liberto
Asst. Prof. in Intelligent Systems, SCSS
Room G.15, O’Reilly Institute ©Trinity College Dublin

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Data

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Internet Data in 60 seconds
Either download or upload (generate) data

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Big data
4
Why now?
GB
242 kB 1.44MB
(x1000000 the
size of an old
floppy disk)
Much more!!
Also, algorithms that can deal with and learn from such large datasets

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Introduction to Programming
A computer needs instructions to do anything!
No instructions -> expensive ornament

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Introduction to Programming
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What is a programming language?
- A programming language is a set of instructions, delivered according to a particular syntax, that
can be used to create a software program.
- In this module we will use Python.
- Like spoken languages, programming languages have rules, such as syntax, that must be learnt.
- Hands-on learning is the best way to learn a new programming language, so write lots of code!

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Introduction to Programming
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- Typical programming languages are called "high-level languages“. This code can be compiled into
a "low-level language," which is recognized directly by the computer hardware
High-level languages
• Easy for humans to learn and use
• E.g., C, C++, Python
• The machine does not understand
these languages directly
Low-level languages
• The machine (e.g., laptop,
smartphone) understands it
• Full control on what the
machine does exactly
Translation step

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Introduction to Programming
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High-level language -> Translation step -> Low-level (machine) language
Translate all code in one go
Create executables (e.g., .exe in
windows; the file you use to launch
an app on your phone) and use
them on any compatible machine
Translate the code one step at a
time. The interpreter is required to
run the software on a machine.
Challenge: the low-level instructions may
change between different types of
machine (e.g., different CPU, laptop vs.
smartphone, different OS)
COMPILED LANGUAGES
e.g., Pascal, C++
INTERPRETED LANGUAGES
e.g., Python, Matlab
This distinction used to be very important.
It’s less important now.

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Programming languages timeline

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Why Python?
Like with a spoken language, we may like a language because it sounds nicer
than another one. Or because we like the alphabet, or maybe because it is
easier to learn for us because it is closer to another language we know.
What we should focus on is “what we can do with it”!
• Amazing set of libraries/tools for ML
• Rich online resources
• Open-source and free!

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What can we do with Python?
Spotify’s backend consists of many
interdependent services, connected by [its]
own messaging protocol over ZeroMQ.
Around 80% of these services are written in
Python.
It all got started, I believe, because the very earliest
Googlers (Sergey, Larry, Craig, …) made a good
engineering decision: “Python where we can, C++
where we must.”

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https://jupyter-notebook.readthedocs.io/en/stable/
https://jupyter.readthedocs.io/en/latest/install/notebook-classic.html
https://anaconda.cloud/tutorials/getting-started-with-anaconda-individual-edition?source=win_installer
Setting up your coding environment
- Windows or Mac OS: run Anaconda Navigator from
the Start menu or application menu
- In Linux: run anaconda-navigator from the terminal

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Anaconda distribution
It installs many packages (libraries and applications) that are useful for ML

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Anaconda distribution

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Anaconda distribution

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Introduction to programming
Pseudocode
PROGRAM makeACupOfTea
IF kettle unplugged
Plug in kettle
END
put water into kettle
press kettle button for boiling water
search for teabag
select teabag
IF teabag is missing
go away disappointed
END
WAIT for water to boil
add water to cup
add teabag to cup
WAIT for the desired time
remove teabag with spoon/fork
add milk or lemon
serve
END camelCase vs snake_case

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Introduction to programming
Pseudocode
ITERATE
WAIT for input x # x can be +1 (incoming bike) or -1 (bike taken)
IF x == 1
availableStands = availableStands-1
availableBikes = availableBikes+1
ELSEIF x == -1
availableStands = availableStands+1
availableBikes = availableBikes-1
END
END
Indentation, comments, variables, conditions

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Introduction to programming
Pseudocode
ITERATE
WAIT for input x # x can be +1 (incoming bike) or -1 (bike taken)
availableStands = availableStands-x
availableBikes = availableBikes+x
END
Indentation, comments, variables, conditions

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Introduction to programming
Pseudocode
ITERATE
WAIT for input x # x can be +1 (incoming bike) or -1 (bike taken)
IF availableStands-x < 0 OR availableStands-x > MAX_STANDS
ERROR
ELSE
availableStands = availableStands-x
availableBikes = availableBikes+x
END
END
Indentation, comments, variables, conditions

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Code examples
https://github.com/ageron/handson-ml2
https://colab.research.google.com/github/ageron/handson-
ml2/blob/master/
From the book “Hands-On Machine Learning with Scikit-Learn,
Keras, and TensorFlow”, Aurélien Géron, 2019
We will also upload our own code on the blackboard

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Introduction to programming
Code: print(“Hello world!”)
Output: Hello world!
Comments # This is a comment
Variables (types) x1 = 5
x2 = “I am a string”
x3 = 3/2
# String concatenation
string1 = "Linux"
string2 = "Hint"
joined_string = string1 + string2
print(joined_string)
Calculating 43
import math
# Assign values to x and n
x = 4
n = 3
# Method 1
power = x ** n
print("%d to the power %d is %d" % (x,n,power))
# Method 2
power = pow(x,n)
print("%d to the power %d is %d" % (x,n,power))
# Method 3
power = math.pow(2,6.5)
print("%d to the power %d is %5.2f" % (x,n,power))

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Introduction to programming
Not just a calculator!
If statement, For loop, Functions
import datetime as dt
hourNow = dt.datetime.now().hour
# Check if the post office is open
if (hourNow >= 8 and hourNow <= 18):
print(“Open")
else:
print(“Closed")
# Alternatively
# if (hourNow in range(8,19))
# Boolean value
val1 = True
print(val1)
# Number to Boolean
number = 10
print(bool(number))
number = -5
print(bool(number))
number = 0
print(bool(number))
# Boolean from comparison operator
val1 = 6
val2 = 3
print(val1 < val2)
True
True
True
False
False

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Introduction to programming
Not just a calculator!
If statement, For loop, Functions, Classes
x = range(6)
for n in x:
print(n)
# Boolean value
val1 = True
print(val1)
# Number to Boolean
number = 10
print(bool(number))
number = -5
print(bool(number))
number = 0
print(bool(number))
# Boolean from comparison operator
val1 = 6
val2 = 3
print(val1 < val2)
True
True
True
False
False

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More about coding
Good code needs little comments. But use comments!
Choose meaningful variable names.
My advice: Top-down coding style
Start by organizing the sections by using pseudocode as comments
# This script prints whether a Dublin-bike station has available bikes now
# Loads the Dublin-bikes real-time dataset
# Ask user which bike station they want to look into
# Extract the most recent information about the station of interest
# If the column ‘Available Bikes’ is greater than zero, then print “Yes”
# Else print “No”

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More about coding
Good code needs little commenting. But use comments!
Choose meaningful variable names.
My advice: Top-down coding style
Start by organizing the sections by using pseudocode as comments
Then start writing each section
# This script prints whether a Dublin-bike station has available bikes now
# Loads the Dublin-bikes real-time dataset
loadataset = pandas.read_csv("dublinbikes_2021Q1.csv")
# Ask user which bike station they want to look into
val = input("Enter the station name: ")
# Extract the most recent information about the station of interest
# If the column ‘Available Bikes’ is greater than zero, then print “Yes”
# Else print “No”

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