Introduction Exploratory data analysis is one of the best practices used in data science today. While starting a career in…
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How to Selectively Scale Numerical Input Variables for Machine Learning
Many machine learning models perform better when input variables are carefully transformed or scaled prior to modeling. It is convenient,…
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Suppose you have a computer that can evaluate and compose continuous functions of one real variable and can do addition.…
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Data preparation involves transforming raw data into a form that is more appropriate for modeling. Preparing data may be the…
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Many machine learning algorithms perform better when numerical input variables are scaled to a standard range. This includes algorithms that…
Continue ReadingHow to Scale Data With Outliers for Machine Learning
Last Updated on May 27, 2020Many machine learning algorithms perform better when numerical input variables are scaled to a standard…
Continue ReadingHow to Use Quantile Transforms for Machine Learning
Numerical input variables may have a highly skewed or non-standard distribution. This could be caused by outliers in the data,…
Continue ReadingDevelop a Model for the Imbalanced Classification of Good and Bad Credit
Misclassification errors on the minority class are more important than other types of prediction errors for some imbalanced classification tasks.…
Continue ReadingHow to Transform Target Variables for Regression With Scikit-Learn
Data preparation is a big part of applied machine learning. Correctly preparing your training data can mean the difference between…
Continue ReadingA Gentle Introduction to Bayesian Belief Networks
Probabilistic models can define relationships between variables and be used to calculate probabilities. For example, fully conditional models may require…
Continue ReadingThe Intuition Behind Correlation
We’ll answer that question in this article. We’ll also develop an intuitive feel for the equation for Pearson’s correlation coefficient.…
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Continue ReadingWhat makes a movie hit a “jackpot”? Learning from data with Multiple Linear Regression
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Continue ReadingAlgorithmic Fairness: It’s Game On!
Algorithmic Fairness: It’s Game On!Janani SridharBlockedUnblockFollowFollowingJun 11The increasing work and research on Artificial Intelligence (AI) applications across industrial functions has resulted…
Continue ReadingPreparing Tabular Data for Neural Networks
You can use a “multi-hot vector” which is exactly the same as a one-hot vector except more than one entry…
Continue ReadingBrute force techniques of variable selection for classification problems
If former is the case, we need to filter variables on the basis of their prediction power or influence on…
Continue ReadingJin Hyun Cheong
Four ways to quantify synchrony between time series dataSample code and data to compute synchrony…Mythbusting Fantasy Premier League: Form over fixturesUsing football…
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Continue ReadingA Systematic Distressed Investing Strategy
A Systematic Distressed Investing StrategyTom YuzBlockedUnblockFollowFollowingMay 9IntroductionFinancial distress and bankruptcy exert significant pressure on corporate management, operations, and suppliers. The…
Continue ReadingMulti-Class classification with Sci-kit learn & XGBoost: A case study using Brainwave data
Multi-Class classification with Sci-kit learn & XGBoost: A case study using Brainwave dataA comparison of different classifiers’ accuracy & performance…
Continue ReadingIntroducing Substrate Smart Contracts with Ink
macro is wrapping its contents with more syntax. // Ink// events!contract { // rest of contract}// Solidityinterface ContractName { //…
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Machine learning for Customer Analytics — 1Customer response prediction using Logistic RegressionVivek VijayaraghavanBlockedUnblockFollowFollowingApr 28ContextPersonal loans are a major revenue generating mechanism for…
Continue ReadingBuild an AWS Serverless application with Python 3.x, Zappa and Docker
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Continue ReadingGoing from scratch to a full-blown Flutter app in two days
Set up Firebase for my project and configure the Android version of the app with it. If that sounds new…
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