Algorithms

[Cheat Sheet] 6 Pillar Machine Learning Algorithms

This machine learning cheat sheet gives you a visual overview of 6 must-know machine learning algorithms (and where to learn more). Linear Regression: train your linear model to predict output values. K-Means Clustering: apply it on unlabeled data to find clusters and patterns in your data. K-Nearest Neighbors: use a similarity metric to find the …

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Logistic Regression in Python Scikit-Learn

Logistic regression is a popular algorithm for classification problems (despite its name indicating that it is a “regression” algorithm). It belongs to one of the most important algorithms in the machine learning space. Linear Regression Background Let’s review linear regression. Given the training data, we compute a line that fits this training data so that …

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Random Forest Classifier with sklearn

Does your model’s prediction accuracy suck but you need to meet the deadline at all costs? Try the quick and dirty “meta-learning” approach called ensemble learning. In this article, you’ll learn about a specific ensemble learning technique called random forests that combines the predictions (or classifications) of multiple machine learning algorithms. In many cases, it …

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SVM sklearn: Python Support Vector Machines Made Simple

Support Vector Machines (SVM) have gained huge popularity in recent years. The reason is their robust classification performance – even in high-dimensional spaces: SVMs even work if there are more dimensions (features) than data items. This is unusual for classification algorithms because of the curse of dimensionality – with increasing dimensionality, data becomes extremely sparse …

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Python Scikit-Learn Decision Tree [Video + Blog]

Decision Trees are powerful and intuitive tools in your machine learning toolbelt. Decision trees are human-readable – in contrast to most other machine learning techniques. You can easily train a decision tree and show it to your supervisors who do not need to know anything about machine learning in order to understand how your model …

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Neural Networks with SKLearn MLPRegressor

Neural Networks have gained massive popularity in the last years. This is not only a result of the improved algorithms and learning techniques in the field but also of the accelerated hardware performance and the rise of General Processing GPU (GPGPU) technology. In this article, you’ll learn about the Multi-Layer Perceptron (MLP) which is one …

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K-Nearest Neighbors (KNN) with sklearn in Python

The popular K-Nearest Neighbors (KNN) algorithm is used for regression and classification in many applications such as recommender systems, image classification, and financial data forecasting. It is the basis of many advanced machine learning techniques (e.g., in information retrieval). There is no doubt that understanding KNN is an important building block of your proficient computer …

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[Tutorial] K-Means Clustering with SKLearn in One Line

If there is one clustering algorithm you need to know – whether you are a computer scientist, data scientist, or machine learning expert – it’s the K-Means algorithm. In this tutorial drawn from my book Python One-Liners, you’ll learn the general idea and when and how to use it in a single line of Python …

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Are Energy Costs and CapEx Invested in Bitcoin Worth It?

Bitcoin capital expenditure and energy overhead are often criticized to be unsustainably high. But are they worth it in relation to the value provided by the Bitcoin network? TLDR; Capex and energy costs are estimated using the USD value of the transaction fees paid by the Bitcoin traders. The value of the Bitcoin monetary system …

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[Google Interview] Find the k-th Largest Element in an Unsorted Array

Do you train for your upcoming coding interview? This question was asked by Google as reported in multiple occasions by programmers all around the world. Can you solve it optimally? Let’s dive into the problem first. Problem Formulation Given an integer array or Python list nums and an integer value k. Find and return the …

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16 PDF Cheat Sheets for Programmers

A couple of years ago, I fell into the habit of creating cheat sheets when exploring certain areas in the programming space. Over time, hundreds of thousands of Finxters have downloaded and used them in their own learning journeys. However, the cheat sheets are largely scattered around many different locations on the Finxter ecosystem. And …

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