Our first step towards the computer vision projects. An introduction to the possibilities with OpenCV image and video processing library.

Photo by My name is Yanick on Unsplash

Short Intro

  • encourage everybody to use the OpenCV library;
  • showcase some of the essential OpenCV capabilities;

Motivation

Even while staying indoors, we can collect and analyze some data (directly from our web camera, for example), right?


What are the common performance evaluation measures? Which metric is the best? Why? Let us talk about these questions in simple terms.

An animation showing a process of evaluating Machine Learning model.
An animation showing a process of evaluating Machine Learning model.
Made by Author. An animation showing a process of evaluating a Machine Learning model.

Intro

  • Classification models predict a discrete value. This includes some classes/labels, such as cats VS. dogs, mushrooms…


Understanding how Artificial Neural Networks (NNs) work under the hood in simple words. Learn about Feedforward and Back Propagation using intuitive animations.

An Artificial Neural Network (in short just NN) is a computing system that tries to mimic the human brain.
An Artificial Neural Network (in short just NN) is a computing system that tries to mimic the human brain.
Made by Author. An Artificial Neural Network (in short just NN) is a computing system that tries to mimic the human brain.

Intro

What is NN?


An overview of Machine Learning classification algorithms. The best algorithm and "No free lunch theorem".

A cover photo for the tutorial on Classification Machine Learning algorithms.
A cover photo for the tutorial on Classification Machine Learning algorithms.
Photo by Ian Taylor on Unsplash

Intro


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 point of SVM is to separate the data into classes by finding a boundary/separator.


Photo by Irena Carpaccio on Unsplash

Introduction & Summary

  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

K-NN algorithm classifies cases based on their similarity to other cases.

K-NN paradigm

Essentially, it comes down to calculating the distance between two data points.


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

I decided to break the ice for everyone who is just starting out on this journey of mastering the Machine Learning.


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


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
  • 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

Ruslan Brilenkov

Certified Data Scientist | Ph.D. candidate in Astrophysics | I write about everything I find fascinating | LinkedIn: http://bit.ly/RBrilenkov

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