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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Zustand: Neu. Neuware - Decision Tree Interview Mastery200+ Questions to Crack Machine Learning InterviewsBreak into machine learning roles with confidence.Decision trees are one of the most frequently tested topics in machine learning interviews, yet many candidates struggle to explain them clearly and apply them correctly under pressure.This book is designed to help you master decision trees from the ground up and turn interview knowledge into real confidence.Learn how to think like an interviewerThis is not just a collection of questions. Each concept is explained in a simple and practical way, helping you understand not only what to say but how to think.You will learn: - How decision trees work step by step- How to explain concepts clearly in interviews- How to avoid common mistakes and trapsWhat you will learn- Core fundamentals and intuition behind decision trees- Gini, entropy, and information gain explained simply- Regression trees and variance reduction- ID3, C4.5, and CART algorithms- Overfitting, pruning, and bias-variance tradeoff- Feature importance and interpretability- Random Forest and boosting- Model evaluation and real-world problem solvingBuilt for real interviewsThis book prepares you for: - Machine learning interviews- Data science interviews- Technical screening rounds- Real-world ML discussionsAvoid common mistakesLearn how to avoid: - Misinterpreting accuracy in imbalanced data- Confusing entropy and Gini- Assuming deeper trees are always better- Misunderstanding Random Forest and boostingWho this book is for- Machine learning beginners- Data science students- Engineers preparing for interviews- Anyone who wants strong fundamentalsIf you want to stand outKnowing answers is not enough. You need to explain clearly, think deeply, and respond with confidence.This book helps you do exactly that.Do not just prepare for interviews. Master them.…

Taschenbuch. Zustand: Neu. Neuware - Regression Model Interview Mastery200+ Questions to Crack Machine Learning InterviewsBreak into machine learning roles with confidenceRegression is one of the most important topics in machine learning interviews. However, many candidates struggle to explain concepts clearly, choose the right models, and solve real-world problems under pressure.This book is designed to help you master regression step by step and build true interview confidence.Learn regression the practical wayThis is not just a theory-heavy book. It is a structured, interview-focused guide that teaches you how to think, explain, and apply concepts in real scenarios.You will learn: - How regression models work in simple terms- How to explain answers clearly in interviews- How to avoid common mistakesWhat you will learn- Linear regression and intuition- Gradient descent and optimization- Loss functions such as MSE, MAE, and RMSE- Multiple regression and feature interpretation- Regularization including Ridge, Lasso, and Elastic Net- Bias and variance tradeoff- Polynomial and nonlinear regression- Regression trees and advanced models- kNN regression and Support Vector Regression- Random Forest and Gradient Boosting- Model evaluation and performance analysisBuilt for interviewsThis book prepares you for: - Machine learning interviews- Data science roles- Technical interview rounds- Real-world problem solvingAvoid common mistakesLearn how to avoid: - Misunderstanding evaluation metrics- Overfitting complex models- Choosing incorrect loss functions- Misinterpreting model resultsWho this book is for- Beginners learning machine learning- Students preparing for interviews- Data science candidates- Professionals improving fundamentalsIf you want to stand outKnowing concepts is not enough. You must be able to explain clearly, think logically, and solve problems confidently.This book helps you achieve that.Do not just prepare for interviews. Master them.…

Taschenbuch. Zustand: Neu. Neuware - Crack the Machine Learning Interview - Part I is the essential starting point for anyone preparing for machine learning interviews seriously.If you've ever felt overwhelmed by the breadth of ML interview prep-math, statistics, algorithms, coding, system design, metrics, and modeling-this book helps you build the right foundation first.This volume focuses on the core knowledge every strong machine learning candidate needs before moving into advanced modeling, deep learning, or system design.This book is designed for: - Machine Learning Engineers- Data Scientists- Applied Scientists- Research Engineers- Software Engineers transitioning into MLRather than giving you shallow definitions or generic textbook summaries, this book teaches you how to think about machine learning concepts the way interviewers expect: clearly, practically, and under real interview conditions.Inside Part I, you'll build a strong base in: - how machine learning interviews really work- how to build an interview preparation strategy that matches your role and timeline- the mathematics that matter most for ML interviews- the statistics concepts that interviewers repeatedly test- machine learning fundamentals and generalization- linear regression and logistic regression- decision trees, random forests, and gradient boosting- support vector machines, k-nearest neighbors, Naive Bayes, PCA, and clusteringThis book is especially useful if you want to: - strengthen weak fundamentals before interview season- move from passive ML knowledge to interview-ready explanation- understand not just what an algorithm is, but when to use it, what its trade-offs are, and how to explain it well- avoid common mistakes candidates make when answering foundational ML questions- build a base solid enough for coding rounds, system design rounds, and real-world ML problem solvingUnlike many interview prep books that jump straight into memorization, this volume emphasizes clarity, reasoning, and practical understanding. Every major topic is framed in the context of how it appears in interviews and how strong candidates are expected to explain it.If you want to become the kind of candidate who sounds thoughtful, technically grounded, and genuinely prepared-not just someone who memorized answers-this is where to start.Start with the foundation. Build the depth. Crack the machine learning interview. …