Machine Learning Project: Decision Tree for Employee Raise Prediction (Full Code)

Learn how to build a decision tree algorithm from scratch in Python! In this tutorial, we'll use real-world employee appraisal data to predict raises with 100% accuracy (on the training set ). We'll cover everything from data preparation to splitting data, choosing features, and evaluating the model. No prior machine learning experience needed! You might also like to watch - Precision, Recall and F1 Score -    • Accuracy, Confusion Matrix, Precision, Rec...   Linear Regression -    • Data Science | How to Make Linear Regressi...   Data Science Playlist -    • Data Science   Statistics for Beginners -    • Statistics   In this video we have covered - 00:00 - Story or context building for Decision Tree use case 01:13 - Understanding the data 01:54 - Importing all the prerequisites 02:23 - Encoding character variables | Feature Engineering 04:08 - Understanding the encoded mapping 07:15 - Train Test Split 08:34 - Building and training the Decision Tree Model 11:00 - Model performance evaluation Tags - Decision Tree Precision Recall F1Score Confusion Matrix Accuracy #Learnerea #DecisionTree #Statistics #Precision #Recall #F1Score #ConfusionMatrix #Accuracy #DataScience #MachineLearning #DeepLearning #ArtificialIntelligence #AI #LinearRegressionInMachineLearning #Logit