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Layman Tutorials in Machine Learning

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Tag: Tutorial

Mapping Global Cuisine with Word Embeddings

November 23, 2021Leave a comment

How can we systemically identify analogous food items across cultures? Learn how using word embeddings.

k-Nearest Neighbors & Anomaly Detection Tutorial

September 14, 2016September 22, 20162 Comments

Do you know what gives red and white wine their colors? Use k-NN to discover the chemical make-up that defines typical types of wines, as well as to detect atypical ones.

Decision Trees Tutorial

July 27, 2016September 22, 20169 Comments

Decision trees can be used to identify customer profiles or to predict who will resign. Using the Titanic dataset, learn about its advantages and pitfalls, as well as better alternatives.

K-Nearest Neighbor (KNN) Tutorial: Anomaly Detection

June 22, 2015September 23, 2016Leave a comment

Outliers can be detected by algorithms used for predictions. To illustrate, we use the k-nearest neighbor (kNN) clustering algorithm.

Topic Modeling with LDA Introduction

June 21, 2015September 23, 201619 Comments

Latent Dirichlet allocation (LDA) is a technique that automatically discovers topics that a set of documents contain. It is used to analyze large volumes of text efficiently. To find out how it works, check out this tutorial.

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About Algobeans

Algobeans is authored by Annalyn Ng (University of Cambridge) and Kenneth Soo (Stanford University). We noticed that while data science is increasingly used to improve workplace decisions, many people do not have a good understanding of how it works. Our goal is to support anyone who wants to get started in data science. Each tutorial covers the important functions and assumptions of a data science technique, without any math or jargon. We also illustrate these techniques with real-world data and examples.

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