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In this guide, we'll be taking a look at an unsupervised learning model, known as a Self-Organizing Map (SOM), as well as its implementation in Python. We'll be using an RGB Color example to train the SOM and demonstrate its performance and typical usage. Self-Organizing Maps: A General Introduction A...
Mehreen Saeed
In this guide, we'll dive into a dimensionality reduction, data embedding and data visualization technique known as Multidimensional Scaling (MDS). We'll be utilizing Scikit-Learn to perform Multidimensional Scaling, as it has a wonderfully simple and powerful API. Throughout the guide, we'll be using the Olivetti faces dataset from AT&...
A* is a heuristic path searching graph algorithm. This means that given a weighted graph, it outputs the shortest path between two given nodes. The algorithm is guaranteed to terminate for finite graphs with non-negative edge weights. Additionally, if you manage to ensure certain properties when designing your heuristic it...
Darinka Zobenica
Spelling mistakes are common, and most people are used to software indicating if a mistake was made. From autocorrect on our phones, to red underlining in text editors, spell checking is an essential feature for many different products. The first program to implement spell checking was written in 1971 for...
Kristina Popovic
The constant growth of data on the Internet creates a demand for tools that process textual information. Moreover, it's highly important that this instrument of text analysis could implement solutions for both low and high-level NLP tasks such as counting word frequencies, calculating sentiment analysis of the texts or detecting...
Natalia Kuzminykh
This tutorial is an introduction to a simple optimization technique called gradient descent, which has seen major application in state-of-the-art machine learning models. We'll develop a general purpose routine to implement gradient descent and apply it to solve different problems, including classification via supervised learning. In this process, we'll gain...
The amount of textual data on the Internet has significantly increased in the past decades. There's no doubt that the processing of this amount of information must be automated, and the TextBlob package is one of the fairly simple ways to perform NLP - Natural Language Processing. It provides a...
Facial detection is a powerful and common use-case of Machine Learning. It can be used to automatize manual tasks such as school attendance and law enforcement. In the other hand, it can be used for biometric authorization. In this article, we'll perform facial detection in Python, using OpenCV. OpenCV OpenCV...
Guest Contributor
Ensemble classification models can be powerful machine learning tools capable of achieving excellent performance and generalizing well to new, unseen datasets. The value of an ensemble classifier is that, in joining together the predictions of multiple classifiers, it can correct for errors made by any individual classifier, leading to better...
Dan Nelson
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