A comprehensive guide to starting practicing Machine Learning (ML) in Python for complete beginners with hands-on examples. Learn ML and Upgrade yourself from a complete beginner → to ML practitioner. Explaining the SVM algorithm.

Photo by Kalineri on Unsplash

Intro

The Support Vector Machine algorithm (or SVM) is a classification algorithm that classifies cases by separating them one from another.

In SVM, data points that are on the one side from that separator belong to one class, and those points on the other side belong to another class.

One might wonder: if we want to classify unknown cases why do not use a classification algorithm that works by classifying the data points directly (such as K-Nearest Neighbors) instead of classifying them by separation?

There are…


A step-by-step complete Data Science project: from Business problem description to solution and implementation (with code). Using Foursquare API, Beautiful soup, Requests, Pandas, and Folium.

Photo by Irena Carpaccio on Unsplash

Introduction & Summary

I created this project in order to complete a Capstone Project to obtain IBM Professional Data Science Certificate. I came up with this business idea because it resonates with me as a promoter of a healthy lifestyle. So I would like to share it with you step-by-step.

The article consists of the following chapters:

  1. Business Problem (Introducing a business idea and my approach to solving it);
  2. Data Analysis (Describing the relevant data and the process…


A comprehensive guide to starting practicing Machine Learning (ML) in Python for complete beginners with hands-on examples. Learn ML and Upgrade yourself from a complete beginner → to ML-practitioner. Explaining the K-NN algorithm.

A cover photo for the article K-Nearest Neighbors. Picture shows Totoro character from the animation “My neighbor Totoro”.
A cover photo for the article K-Nearest Neighbors. Picture shows Totoro character from the animation “My neighbor Totoro”.
Photo by Raychan on Unsplash

Intro

The K-Nearest Neighbors algorithm (or K-NN) is a classification algorithm that takes a batch of labeled points and uses them to learn how to label other points.

In K-Nearest Neighbors, data points that are close to each other are said to be neighbors.

K-NN paradigm

Similar cases with the same class labels are close to each other in the feature space. Thus, the distance between the two cases is a measure of their similarity or conversely, their dissimilarity.

For…


A comprehensive guide to starting practicing Machine Learning (ML) in Python for complete beginners with hands-on examples. Learn ML and Upgrade yourself from a complete beginner → to a ML-practitioner. Explaining the basics, motivation, and tools for Machine Learning.

Cover Photo of a girl with a robot.
Cover Photo of a girl with a robot.
Photo by Andy Kelly on Unsplash

Intro

Hi there! A while ago, I have been talking to a friend and the topic touched on Machine Learning. And by the end of the conversation, I concluded that many people have some prejudice against the whole topic of “intellectual machines”, or even might be afraid to start the learning process due to the overwhelming amount of information. So,

Let us be clear — Machine Learning is not Magic. Machine Learning (so-called ML) is the study of computer algorithms…


This tutorial is the starting point of my big project — “From Zero to a Machine Learning (ML) practitioner”. The main idea is to teach everybody Python and ML despite their educational background.

Cover photo to the article.
Cover photo to the article.
Photo by rishi on Unsplash

This tutorial is meant for everyone interested in Python. Especially, for those who are just starting out and cannot break the ice from intention to action. You are here which means you are serious about learning Python and I appreciate it.

I am using Python for my work a lot. Some of the applications are scientific computing, statistics, and advanced visualization. But in my free time, I enjoy creating mini-applications for various reasons. Some of them solve a particular problem (personal, or a world large-scale problem), others are just for fun, or just something to challenge myself.

This particular lesson…


Unsupervised Machine Learning in Python from scratch tutorial

Messier 13 — the Great Globular Cluster in Hercules. The best known globular clusters in the northern hemisphere.
Messier 13 — the Great Globular Cluster in Hercules. The best known globular clusters in the northern hemisphere.
Photo by Guillermo Ferla on Unsplash

After the short introduction to clustering and the practical ideas of using it, we will go through this tutorial on K-Means Clustering from scratch in Python. I will show you how it works intuitively step by step, in a way I wish somebody showed it to me. After completing this tutorial, you will learn how to:

  • generate a dataset using sklearn make_blobs function,
  • visualize the data with matplotlib,
  • understand & create your own K-Means Clustering algorithm from scratch using only numpy, a basic Python library,
  • create an animated image (.gif) using imageio library.

Introduction

Customer Segmentation

Imagine that we are a company that…


Python for time management. Pomodoro application. The full code is included :)

A laptop and a cup. The header image for my article about creating a productivity app from scratch with Python.
A laptop and a cup. The header image for my article about creating a productivity app from scratch with Python.
Photo by Artem Sapegin on Unsplash

Intro

This article is the second part of my project I discussed previously. To recap, the idea is to create a Pomodoro app in Python from scratch. Because we all want to be effectively productive while staying at home amidst the COVID-19 pandemic.

One way to do so is to take one step at a time. Because our brain is not meant to be multitasking. In reality, it does multi-switching between different tasks.

Summary from Part 1

Previously, we built the base…


Applying Regular Expressions (regex) to a real-world problem.

A laptop with a face mask on it.
A laptop with a face mask on it.
Photo by Guido Hofmann on Unsplash

Short Intro

The idea behind this project is very simple yet meaningful. It boils down to the following questions:

What can I do for the community during this horrible pandemic? How can I help others to research the coronavirus?

I am going to apply my knowledge of Python to analyze a scientific paper on COVID-19 and to show you that everyone can use Python to analyze the text and get some insights out of it. This post is meant to encourage everyone to use Python in day-to-day life. …


Python for time management. Pomodoro application.

Woman with a laptop sitting on a chair.
Woman with a laptop sitting on a chair.
Photo by Daria Nepriakhina on Unsplash

Introduction

The pandemic is hitting hard. It is necessary to limit any physical contact with the “outside” world and to stay indoors as much as possible. If you have an opportunity to work from home, it is great. However, there is a price to pay as well.

Staying efficiently productive at home is not an easy task. A home environment is not a work environment. Assuming you are not living alone, you cannot just say bye to your kids/family for the next ~8 hours and leave the house for work. Often, the workplace is the same room where you rest, eat…


Introduction to the Tkinter.

Woman on the sofa with a laptop
Woman on the sofa with a laptop
Photo by Mimi Thian on Unsplash

Intro

Python is my favorite programming language. It is easy to get around, versatile, yet powerful. Python is a great choice for both beginners and experts. There are numerous reasons for using Python. In my opinion, one of the main reasons is an enormous amount of open-source Python libraries, packages, and frameworks.

There are many articles describing the advantages of Python. For example, as was mentioned by Mindfire Solutions in 7 Important Reasons Why You Should Use Python article: “You can use Python for developing complex scientific and numeric applications. Python is designed with features to facilitate data analysis and visualization.”

Ruslan Brilenkov

Ph.D. candidate in Astrophysics | I write about everything I find fascinating.

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