🧠 ML/AI Workshop @ What After College

~Anish Sachdeva

Workshop Timings

Workshop Dates: 24th, 25th, 28th, 29th & 30th December 2020
Workshop Timings: 3:00 PM - 8:00 PM
Break Timings: 5:00 PM - 6:00 PM

🌐 Course Link | 📽 Class Video Recordings | 🌊 Course Flow | ✒ MS Exam Sample 1 | ✒ MS Exam Sample 2

📖 Index

1. Introduction
2. Getting Started With Python
3. Day 1
4. Day 2
5. Day 3
6. Day 4
7. Day 5
8. Further Reading
9. Python Books
10. Machine Learning Books
11. Future Path??

Introduction

Solutions to all sample problems on HackerRank under the Python domain can be looked up here.

Programming is a very hands process and is both an art as well as a science. We are engineers and are required to create efficient solutions but at the same time our programs should be highly readable and flexible and all the other snappy terms which makes it an art as well.

To become proficient in this art, there are many resources, and books and tutorials. Each has it's merit and making the first step in any direction is commendable, but the cardinal factor at the end of the day will be you sitting down (or standing) and writing code. No book or resource can substitute that.

So, what are you waiting for 😀😉 - try as many questions (below or otherwise) as you can.... 🐱‍👤
Happy Coding 🐱‍💻

You can stalk your instructor on LinkedIn, GitHub & Instagram.

Getting Started With Python

We need to install and configure a few things before we can write and run any Python code. To write Python code we need the Python interpreter on our machine.

1. Install the Python 3 Interpreter

To write python programs on your machine we need the Python interpreter. There are 2 popular versions of Python out there right now Python 2 and Python 3. There are breaking changes between these versions and this course will be taught in Version 3. So as long as you have python version 3.{something}.{something} you're good to go 🙂

Download python from this website 🌐.

To check that python has been correctly installed on your machine run the following command on your terminal:

python --version

It should have an output akin to:

Python 3.8.3 

Once that Python has been successfully installed, we need to install a code editor or IDE so that we can write programs and run them. I suggest using VS Code if you prefer a Code editor over an IDE (or if you don't know the difference between Code editor and IDE 😉). using a code editor will aso be less intensive on computing resources.

I personally prefer the JetBrains PyCharm, but warning ⚠ it is a heavy software and might not run properly on all machines (especially laptops that are constrained for resources).

2. Installing VS Code (or go to step 3 - Installing PyCharm)

1. Download the setup from here.
2. Run the setup which is pretty straight forward. Just click next like 10 times and voila!

3. Installing JetBrains PyCharm

1. You can either install the educational edition (free) from here.
2. Or you can create an account on JetBrains if you have a university email address and then install the JetBrains Toolbox.
3. You can easily manage JetBrains IDE's and projects using the ToolBox app. From the ToolBox app you can now install either IntelliJ PyCharm Edu Edition or Ultimate Edition.

4. Installing git (Optional - Only required for Windows users)

This is an optional step of your getting started guide and can be skipped. Although installing git and using it in your projects is highly recommended. For a learning path to learn git have a look at the Future Path + Scope section.

Install git from the git-scm website. Run the setup and click next like 10 times and use the recommended settings for installation.

There will be a section when it will ask the standard text editor and gie you an option between Vim and nano. If you are not familiar with Vim then opt for nano.

IMPORTANT Opt for nano if not familiar with Vim.

To check your installation of git check that git bash has been intalled and run the following command on your terminal.

git --version

The output should be akin to

git version 2.24.1.windows.2

5. Writing your first Python Program

Open your text editor/IDE and create a new file hello_world.py and in that file copy paste the following code snippet.

print('hello world !')

To run the code navigate to file in terminal and run the following commands.

python hello_world.py
>>> hello world !

1️⃣ Day 1

• Hello World!
• Print Statement
• Comments
• Variables Names
• Variables
• Taking User Input
• Taking Integer Input
• Arithmetic Operators
• Boolean Operators
• If Else Block
• Even Odd Program
• Ternary Operator
• While Loop
• Sum N Natural Numbers Using While Loop
• Range Object
• Operator Shorthand
• For Loops
• Sum N Natural Numbers
• Sum Of Squares
• Factorial Using For Loop
• Functions
• Factorial Function
• Factorial Recursive Function
• Fibonacci Recursive Function
• Lists

2️⃣ Day 2

• Helping 1 Person In His Problem
• Loop Control Flow Statements
• Lists
• Iterating Over a List
• List Comprehension (Generator Functions)
• Taking List Input
• Map Operator
• Tuples
• Dictionary
• Complex Dictionary
• Frequency Counter Using Dictionary
• Iterating Over a Dictionary
• Inbuilt Functions
• Math Package
• Random Package
• NumPy Tutorial (Jupyter Notebook)
• Matplotlib Tutorial (Jupyter Notebook)
• Drawing Multiple Plots

3️⃣ Day 3

• Introduction to Pandas Tutorial (Jupyter Notebook)
• Working With The Stack Overflow Data Using Pandas (Jupyter Notebook)
• Plotting Pandas Data Using Matplotlib (Jupyter Notebook)
• String Functions
• sWAP cASE (Hackerrank)
• Lambda Functions
• String Formatting in Python
• Leap Year Problem (Hackerrank)

4️⃣ Day 4

• Vectorization (Jupyter Notebook)
• Decision Trees (Jupyter Notebook)
• Kaggle Titanic Solution (Jupyter Notebook)
• Linear Regression (Jupyter Notebook)
• Multi Linear Regression (Jupyter Notebook)
• Logistic Regression (Jupyter Notebook)

5️⃣ Day 5

• Nested For Loop
• Ice Cream Parlour (Hackerrank)
• Instagram User Profile Downloader
• Numpy Basics For Deep Learning (Jupyter Notebook)
• Logistic Regression As A Neural Network (Jupyter Notebook)
• Planar Classification With 1 Hidden Layer (Jupyter Notebook)
• Building Neural Network Step By Step (Jupyter Notebook)
• Deep Neural Network Application (Building a Neural Network Classifier) (Jupyter Notebook)

Further Reading

• w3 School Python
• HackerRank python Domain
• Why is it called Python?
• Projects Created on Python
• C++ vs. Java vs. Python Language Speed Test (Informal)
• Math Module
• Stack Overflow Survey 2020
• Python Example Projects and Project Based Tutorials
• Django: Web Development on Python
• Falcon: Minimalist Web Framework

Python Books 📕

• Python Crash Course
• Python in a Nutshell
• Programming Python

Machine Learning Books

• Python For Data Analysis
• Deep Learning With Python ~Francois Chollet

Future Scope and Path

Now that you have learnt the basics of Python and also built an amazing project that showcases your skills, how to move ahead and learn more? What else could you work on? Here are a few suggestions:

Data Structures and Algorithms

Data Structures and Algorithms is an immensely important topic required for Software development and is used by organizations for all sizes as a tool for employee hiring and recruitment. To get better at this I recommend that you practice questions in the Data Structures and Algorithms domain on HackerRank and you can have a look at solutions to many of those problems in the solution repositories given below.

Problem Domain	Solution Repository
Data Structures	Solutions
Algorithms	Solutions

You can views solutions to problems in Python (or any of your preferred programming language) and you are most welcome to contribute to the repository solutions to unsolved problems or solutions in more languages (aka Python).

You can also try questions on Leet Code and have a look at the solutions repository and are most welcome to contribute just as above 😀

Core Python

Before starting of your journey in Data Structures or web development or even machine learning another good first step can be just developing your core Python skills further so that you are familiar with all the different constructs that the language has to offer. That can be done on HackerRank in the Python Domain and you can have a look at solutions to all the problems here.

Web Development

Python is a very versatile programming language and is being used for all things from biology to robotics, computer vision and even serve side rendered web applications and api's. As you are now proficient with the programming language you can start learning a web development framework like Django or Falcon.

Django is a have all web development framework and you can even build very large, highly modern cluster based web sites that can be deployed to scale. You can use it just to create a server-side API with a separate client facing application or a MVC (Model view controller) based application that has server side rendering.

Falcon is a relatively light weight web development platform but it is blazing fast ⚡ and that serves it's own purpose. It can be used to create a super fast very minimalistic server side API's and can aso be used to create server side job runners like mail sending and background processing.

You could always use multiple server side frameworks which will give you the perfect opportunity to use buzz words like docker, kubernetes 🛳, clusters, swarms and add all these buzz words to your resume 😉.

Machine Learning 🔥

Speaking of buzz words... Machine Learning has enjoyed fame of meteoric proportions and there are plenty of resources to get started with ML and Python has somehow become the defacto language used in Machine Learning / Deep Learning applications and is being sed by Engineers & scientists of many different domains that have written numerous libraries serving various purposes all around the globe 🌎 which is good for us ☺.

Some popular libraries are:

• numpy
• scikit-learn
• tensorflow
• open-cv
• pyTorch

To get started with Machine Learning I recommend the ubiquitous Machine Learning by Stanford course on Coursera by Andrew Ng.

This may be old but it's essence and relevance haven't dwindled at all. Solutions to all problems with well written code can be found here.

Learning Git

This is not very correlated to Java, but Git is a technology being used by all organizations big and small that wish to maintain their code over teams of varied sizes and manage projects. Even this repository which you are currently reading in is being maintained by git & has been deployed on github.

Being proficient with git and version control will help you manage all your projects, be in any language Java, Python, C++ and even non-programming projects very efficiently and you will be able to easily maintain project state over all your devices.

There is an excellent Version Control with Git course on Coursera by Atlassian or you can even try this Git Introductory 30min Video on YouTube to learn the basics of git.

So, what are you waiting for git started 😁 (bad pun!)