data science

Data Science Project Completed in 5 Minutes Using ChatGPT Plugin Noteable Automating your data science workflow using ChatGPT plugin Noteable

Data Science Project Completed in 5 Minutes Using ChatGPT Plugin Noteable

The ChatGPT plugin Noteable is a revolutionary tool designed to streamline and enhance the process of data analysis and modeling. Noteable allows users to describe in natural language what they want to do, such as the data analysis techniques they want to use, and it generates a complete notebook using Python, SQL, or markdown as …

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Top 10 Deep Learning Concept Interview Questions and Answers Neural network model terms for data scientist and machine learning engineer interviews

Top 10 Deep Learning Concept Interview Questions and Answers

Deep learning (DL) terminologies are frequently asked during data science and machine learning interviews. In this tutorial, we will discuss the top 10 neural network model concept interview questions and how to answer them. Resources for this post: Let’s get started! Question 1: What is weight initialization for a neural network model? In the python code …

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Top 7 Support Vector Machine (SVM) Interview Questions for Data Science and Machine Learning

The support vector machine (SVM) model is a frequently asked interview topic for data scientists and machine learning engineers. In this tutorial, we will talk about the top 7 support vector machine (SVM) interview questions and how to answer them. The 7 questions are: Resources for this post: Let’s get started! Question 1: How does …

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Imbalanced Multi-Label Classification: Balanced Weights May Not Improve Your Model Performance Compare the random forest model and logistic regression model with and without balanced weights on imbalanced multi-class classification

Imbalanced Multi-Label Classification: Balanced Weights May Not Improve Your Model Performance

The balanced weight is a widely used method for imbalanced classification models. It penalizes the wrong predictions about the minority classes by giving more weight to the loss function. In this tutorial, we will talk about how to use balanced weight for the imbalanced multi-label classification. We will cover the following: If you are interested …

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Isolation Forest For Anomaly Detection And Imbalanced Classification

Isolation Forest For Anomaly Detection

Isolation forest uses the number of tree splits to identify anomalies or minority classes in an imbalanced dataset. The idea is that anomaly data points take fewer splits because the density around the anomalies is low. Python’s sklearn library has an implementation for the isolation forest model. Isolation forest is an unsupervised algorithm, where the …

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One Class SVM Anomaly Detection

One-Class Support Vector Machine (SVM) For Anomaly Detection

One-Class Support Vector Machine (SVM) is an unsupervised model for anomaly or outlier detection. Unlike the regular supervised SVM, the one-class SVM does not have target labels for the model training process. Instead, it learns the boundary for the normal data points and identifies the data outside the border to be anomalies. In this post, …

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LASSO (L1) vs Ridge (L2) vs Elastic Net Regularization for Classification Model

LASSO (L1) vs Ridge (L2) vs Elastic Net Regularization for Classification Model

LASSO (Least Absolute Shrinkage and Selection Operator) is also called L1 regularization, and Ridge is also called L2 regularization. Elastic Net is the combination of LASSO and Ridge. All three are techniques commonly used in machine learning to correct overfitting. In this tutorial, we will cover Resources for this post: Step 0: LASSO (L1) vs …

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Local Outlier Factor (LOF) For Anomaly Detection

Local Outlier Factor (LOF) For Anomaly Detection

Local Outlier Factor (LOF) is an unsupervised model for outlier detection. It compares the local density of each data point with its neighbors and identifies the data points with a lower density as anomalies or outliers. In this tutorial, we will talk about Resources for this post: Step 1: Import Libraries The first step is …

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