Category: Machine Learning

This webpage provides concise machine learning tutorials that cater to both beginners and experienced users. The tutorials cover fundamental concepts required for learning the model, as well as advanced techniques. Specifically, the tutorials focus on machine learning with Python, algorithms, pattern recognition, regression, Random Forest Classifier, Random Forest explained, feature importance, and more.

Bioinformatics • Data Analysis • Machine Learning

The Interval Scheduling Algorithm and its Applications

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12 de February de 2023

This tutorial talks about the Interval scheduling algorithm presents a Python version of it and shares its applications in real-life.

Bioinformatics • Machine Learning

Non-negative Least Squares: Applications and its Use in Python

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12 de February de 2023

This blog post talks about non-negative least squares and its use in bioinformatics, and how to use the method with Python.

Machine Learning

k-means-python

Painless Kmeans in Python – Step-by-Step with Sklearn

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8 de April de 2021

This tutorial shows how to use k-means clustering in Python using Scikit-Learn, installed using bioconda.

Machine Learning • Python

python r squared

Simple R Squared Calculation in Python

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12 de March de 2021

This short tutorial shows how to find the R squared value in Python using sklearn, which can be helpful when looking at the data correlation in …

Machine Learning

Painless Random Forest Regression in Python - Step-by-Step with Sklearn

Painless Random Forest Regression in Python – Step-by-Step with Sklearn

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5 de April de 2020

This tutorial demonstrates a step-by-step on how to use the Sklearn Python Random Forest package to create a regression model.

Machine Learning

Simple Near-duplicate String Detection

Simple Near-duplicate String Detection with LSH

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9 de February de 2020

This tutorial teaches you how to use Locality Sensitive Hashing (LSH) to detect near-duplicate sentences. Moreover, the task of identifying similar sentences is a common task …

Machine Learning

The 2 Most Important Use for Random Forest

The 2 Most Important Use for Random Forest

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17 de January de 2020

This tutorial demonstrates how to use the Sklearn Random Forest (a Python library package) to create a classifier and discover feature importance.

Bioinformatics • Data visualization • Machine Learning

Data Science Careers carving our professional paths

Data Science Careers carving our professional paths

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2 de January de 2020

Data science (or part of any of the data science careers) applies statistical procedures ranging from data transformations, data modeling, statistical and machine learning modeling, and …