Demystifying the Random Forest
Deconstructing and Understanding this Beautiful Algorithm- 27172Murphy ≡ DeepGuide
Linear Discriminant Analysis (LDA) Can Be So Easy
An Interactive Visualisation for You to Experiment With- 26276Murphy ≡ DeepGuide
Cracking the Employee Attrition Problem with Machine Learning
Why it's not a simple problem- 23597Murphy ≡ DeepGuide
A Practical Approach to Evaluating Positive-Unlabeled (PU) Classifiers in Business Analytics
An approach for evaluating PU models with common classification metrics adjusted for the prior probability of the positive class- 22655Murphy ≡ DeepGuide
An ImPULSE to Action: A Practical Solution for Positive Unlabelled Classification
We introduce an approach called ImPULSE Classifier with improved performance on balanced and imbalanced PU data compared to other...- 29349Murphy ≡ DeepGuide
From Evaluation to Enlightenment: Delving into Out-of-Sample Predictions in Cross-Validation
Understanding cross-validation and applying it in practical daily work is a must-have skill for every data scientist. While the primary purpose of cross-validation is to assess model performance and fine-tune hyperparameters, it offers additional outputs- 28806Murphy ≡ DeepGuide
Data-Driven Dispatch
Using supervised learning to predict service callouts to Chicago car collisions- 23737Murphy ≡ DeepGuide
Text Classification with Transformer Encoders
Step-by-step explanation of utilizing Transformer encoders to classify text- 22113Murphy ≡ DeepGuide
Ensemble of Classifiers: Voting Classifier
Combine many different models for better Prediction- 20446Murphy ≡ DeepGuide
Classification With Rosenblatt's Perceptron
The "hello-world" of machine learning- 22730Murphy ≡ DeepGuide
Coin Counting using Lang-SAM
Leverage Lang-SAM for precise coin segmentation in images, followed by a custom neural network to identify and sum their monetary values.- 21471Murphy ≡ DeepGuide
Introduction to Support Vector Machines - Motivation and Basics
Learn basic concepts that make Support Vector Machine a powerful linear classifier- 29222Murphy ≡ DeepGuide
Achieve Better Classification Results with ClassificationThresholdTuner
A python tool to tune and visualize the threshold choices for binary and multi-class classification problems- 28084Murphy ≡ DeepGuide
Logistic Regression, Explained: A Visual Guide with Code Examples for Beginners
Finding the perfect weights to fit the data in- 21671Murphy ≡ DeepGuide
Conformal Prediction for Machine Learning Classification -From the Ground Up
Implementing conformal prediction for classification without need of bespoke packages- 22187Murphy ≡ DeepGuide
From the Perceptron to Adaline
Setting the foundations right- 23749Murphy ≡ DeepGuide
Classifying Source code using LLMs – What and How
Sharing our experience at making LLM-based Source Code classifier- 30003Murphy ≡ DeepGuide
From Adaline to Multilayer Neural Networks
Setting the foundations right- 28770Murphy ≡ DeepGuide
Binary Classification
Unpacking the Real Significance and Limitations of Traditional Metrics- 29234Murphy ≡ DeepGuide
Choosing the Right Number of Neighbors (k) for the K-Nearest Neighbors (KNN) Algorithm
Six methods to measure the effect of the number of neighbors on KNN model evaluation- 24187Murphy ≡ DeepGuide
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We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag