Machine Learning Handwritten Notes Regression & Classification Algorithms

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Machine Learning Handwritten Notes:: Regression & Classification Algorithms
English | October 12, 2026 | ASIN: B0HMSFLNL7 | 52 Pages | Epub | 3.75 MB
Machine Learning Handwritten Notes - Part 2: Regression & Classification AlgorithmsTake your machine learning journey further with clear, student-friendly handwritten notes covering the essential regression and classification algorithms used in machine learning.Prepared by Shishir Singh, M.Tech (AI) student at IIT Bhubaneswar, these notes are designed to make complex concepts easier to understand through a step-by-step learning approach. Whether you are learning algorithms for the first time or revising important concepts before an exam, interview, or placement, this book offers a convenient study companion.What You'll Learn in This Book1. Regression AlgorithmsLinear and Multiple Linear RegressionPolynomial RegressionAssumptions of Linear RegressionGradient DescentStochastic and Mini-Batch Gradient DescentRidge Regression (L2 Regularization)Lasso Regression (L1 Regularization)Elastic Net RegressionBias-Variance Tradeoff2. Regression Evaluation MetricsImportant metrics for evaluating regression modelsUnderstanding model performance and prediction errors3. Classification AlgorithmsLogistic Regression: Perceptron Trick, Sigmoid Function and Loss FunctionSoftmax RegressionNaive BayesK-Nearest Neighbours (KNN)Support Vector Machine (SVM)Decision Trees4. Classification Evaluation MetricsImportant classification metricsROC Curve and AUCUnderstanding how classification models are evaluatedWho Should Read This Book?Students preparing for machine learning exams and technical interviewsB.Tech and M.Tech students studying Artificial Intelligence, Data Science or Computer ScienceBeginners learning regression and classification algorithmsCandidates preparing for AI/ML internships, placements and entry-level rolesLearners who want a structured resource for revision and concept reinforcementWhy Choose These Notes?Machine learning becomes easier when concepts are studied systematically. These notes are intended to support your learning process by bringing important algorithms and evaluation concepts together in one study resource.Use this book for focused revision, strengthen your understanding of fundamental ML algorithms, and build a foundation for exploring more advanced machine learning techniques.Part of a Three-Part Learning SeriesMachine Learning Handwritten Notes - Part 2 focuses on regression and classification algorithms. Read it alongside the other parts of the series for a broader machine learning learning path.Note: This is an independent set of personal study notes prepared by Shishir Singh. It is not an official publication of CampusX.​

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