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  • Supervised vs Unsupervised vs Reinforcement Learning

Supervised vs Unsupervised vs Reinforcement Learning

Supervised vs Unsupervised vs Reinforcement Learning

Machine learning has three core approaches, and understanding how they differ helps you choose the right one for a given problem.

Supervised learning uses labeled data to predict known outcomes. Unsupervised learning uses unlabeled data to discover hidden patterns. Reinforcement learning uses rewards and penalties to teach an agent the best actions over time.

Type

Data Used

Goal

Example

Supervised LearningLabeled dataPredict known outcomesSpam email detection
Unsupervised LearningUnlabeled dataDiscover hidden patternsCustomer segmentation
Reinforcement LearningRewards and penaltiesLearn best actions over timeGame playing AI

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Machine Learning Tutorial

AP

Abhishek Pati

Machine Learning Tutorial

MODULE 1 : Introduction to Machine Learning
lessonWhat is Machine Learning
lessonTypes of Machine Learning
lessonSupervised vs Unsupervised vs Reinforcement Learning
lessonApplications of Machine Learning in Real Life
lessonMachine Learning vs Artificial Intelligence vs Deep Learning
lessonMachine Learning Life Cycle Explained
lessonHow to Set Up Your Machine Learning Environment
MODULE 2 : Python for Machine Learning
lessonPython Basics for Machine Learning
lessonNumPy Basics for Machine Learning
lessonPandas Basics for Data Handling
lessonData Visualization with Matplotlib
lessonData Visualization with Seaborn
MODULE 3 : Data Preprocessing and Feature Engineering
lessonWhat is Data Preprocessing
lessonData Cleaning Techniques
lessonHandling Missing Values
lessonFeature Scaling Explained
lessonNormalization vs Standardization
lessonEncoding Categorical Data
lessonFeature Selection Techniques
lessonFeature Engineering Explained
lessonTrain-Test Split Explained
lessonCross-Validation Explained
MODULE 4 : Supervised Learning: Regression
lessonWhat is Regression in Machine Learning
lessonSimple Linear Regression Explained
lessonMultiple Linear Regression Explained
lessonRidge Regression Explained
lessonLasso Regression Explained
lessonBias and Variance Tradeoff Explained
lessonEvaluation Metrics for Regression Models
MODULE 5 : Supervised Learning: Classification
lessonWhat is Classification in Machine Learning
lessonLogistic Regression Explained
lessonK-Nearest Neighbours Explained
lessonDecision Tree Classifier Explained
lessonRandom Forest Classifier Explained
lessonSupport Vector Machine Explained
lessonModel Selection Techniques
lessonEvaluation Metrics for Classification Models
lessonConfusion Matrix Explained
lessonPrecision, Recall, F1 Score and ROC AUC Explained
MODULE 6 : Unsupervised Learning
lessonWhat is Unsupervised Learning
lessonK-Means Clustering Explained
lessonHierarchical Clustering Explained
lessonPrincipal Component Analysis Explained
lessonDimensionality Reduction Techniques
MODULE 7 : Ensemble Learning
lessonWhat is Ensemble Learning
lessonBagging Explained
lessonBoosting and AdaBoost Explained
lessonGradient Boosting Explained
lessonXGBoost Explained
MODULE 8 : Model Evaluation and Optimization
lessonOverfitting and Underfitting Explained
lessonRegularization Techniques Explained
lessonHyperparameter Tuning and Grid Search Explained
MODULE 9 : Neural Networks and Deep Learning
lessonWhat is a Neural Network
lessonActivation Functions Explained
lessonGradient Descent Explained
lessonWhat is Deep Learning
lessonTensorFlow and Keras Explained
MODULE 10 : Model Deployment
lessonWhat is Model Deployment
lessonSaving and Loading Machine Learning Models
MODULE 11 : Iris Flower Classification
lessonProject Overview and Problem Statement
lessonUnderstanding the Iris Dataset
lessonLoading the Dataset with Pandas
lessonExploratory Data Analysis on Iris Data
lessonSplitting Data into Train and Test Sets
lessonBuilding a K-Nearest Neighbours Model
lessonEvaluating Model Performance
lessonConclusion and Key Takeaways
MODULE 12 : Learning Resources and Next Step
lessonWhat to Learn After This Machine Learning Tutorial
lessonBest Machine Learning Courses

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Machine Learning Tutorial

    MODULE 1 : Introduction to Machine Learning
    lessonWhat is Machine Learning
    lessonTypes of Machine Learning
    lessonSupervised vs Unsupervised vs Reinforcement Learning
    lessonApplications of Machine Learning in Real Life
    lessonMachine Learning vs Artificial Intelligence vs Deep Learning
    lessonMachine Learning Life Cycle Explained
    lessonHow to Set Up Your Machine Learning Environment
    MODULE 2 : Python for Machine Learning
    lessonPython Basics for Machine Learning
    lessonNumPy Basics for Machine Learning
    lessonPandas Basics for Data Handling
    lessonData Visualization with Matplotlib
    lessonData Visualization with Seaborn
    MODULE 3 : Data Preprocessing and Feature Engineering
    lessonWhat is Data Preprocessing
    lessonData Cleaning Techniques
    lessonHandling Missing Values
    lessonFeature Scaling Explained
    lessonNormalization vs Standardization
    lessonEncoding Categorical Data
    lessonFeature Selection Techniques
    lessonFeature Engineering Explained
    lessonTrain-Test Split Explained
    lessonCross-Validation Explained
    MODULE 4 : Supervised Learning: Regression
    lessonWhat is Regression in Machine Learning
    lessonSimple Linear Regression Explained
    lessonMultiple Linear Regression Explained
    lessonRidge Regression Explained
    lessonLasso Regression Explained
    lessonBias and Variance Tradeoff Explained
    lessonEvaluation Metrics for Regression Models
    MODULE 5 : Supervised Learning: Classification
    lessonWhat is Classification in Machine Learning
    lessonLogistic Regression Explained
    lessonK-Nearest Neighbours Explained
    lessonDecision Tree Classifier Explained
    lessonRandom Forest Classifier Explained
    lessonSupport Vector Machine Explained
    lessonModel Selection Techniques
    lessonEvaluation Metrics for Classification Models
    lessonConfusion Matrix Explained
    lessonPrecision, Recall, F1 Score and ROC AUC Explained
    MODULE 6 : Unsupervised Learning
    lessonWhat is Unsupervised Learning
    lessonK-Means Clustering Explained
    lessonHierarchical Clustering Explained
    lessonPrincipal Component Analysis Explained
    lessonDimensionality Reduction Techniques
    MODULE 7 : Ensemble Learning
    lessonWhat is Ensemble Learning
    lessonBagging Explained
    lessonBoosting and AdaBoost Explained
    lessonGradient Boosting Explained
    lessonXGBoost Explained
    MODULE 8 : Model Evaluation and Optimization
    lessonOverfitting and Underfitting Explained
    lessonRegularization Techniques Explained
    lessonHyperparameter Tuning and Grid Search Explained
    MODULE 9 : Neural Networks and Deep Learning
    lessonWhat is a Neural Network
    lessonActivation Functions Explained
    lessonGradient Descent Explained
    lessonWhat is Deep Learning
    lessonTensorFlow and Keras Explained
    MODULE 10 : Model Deployment
    lessonWhat is Model Deployment
    lessonSaving and Loading Machine Learning Models
    MODULE 11 : Iris Flower Classification
    lessonProject Overview and Problem Statement
    lessonUnderstanding the Iris Dataset
    lessonLoading the Dataset with Pandas
    lessonExploratory Data Analysis on Iris Data
    lessonSplitting Data into Train and Test Sets
    lessonBuilding a K-Nearest Neighbours Model
    lessonEvaluating Model Performance
    lessonConclusion and Key Takeaways
    MODULE 12 : Learning Resources and Next Step
    lessonWhat to Learn After This Machine Learning Tutorial
    lessonBest Machine Learning Courses

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    HCL GUVI (Grab Your Vernacular Imprint) Geek Network Private Limited is a leading online learning and skills development company, incubated by IIT Madras and IIM Ahmedabad.

    Established in 2014 and acquired by the HCL Group in 2022, HCL GUVI is dedicated to providing effective and high-quality learning and skilling programs that transcend language barriers in technology education. HCL GUVI today is trusted by over 4.8 million users, 20 languages and 2500+ corporate partners.

    app storeplay store
    Refer & Earn

    HCL GUVI (Grab Your Vernacular Imprint) Geek Network Private Limited is a leading online learning and skills development company, incubated by IIT Madras and IIM Ahmedabad.

    Established in 2014 and acquired by the HCL Group in 2022, HCL GUVI is dedicated to providing effective and high-quality learning and skilling programs that transcend language barriers in technology education. HCL GUVI today is trusted by over 4.8 million users, 20 languages and 2500+ corporate partners.

    app storeplay storeRefer & Earn
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