Mastering Machine Learning Through Questions and Answers Rohan Banerjee, Uddalok Sen
- Autorzy:
- Rohan Banerjee, Uddalok Sen
- Wydawnictwo:
- BPB Publications
- Ocena:
- Stron:
- 354
- Dostępne formaty:
-
ePubMobi
Opis
książki
:
Mastering Machine Learning Through Questions and Answers
Machine learning has become a cornerstone of modern technology, driving innovations across industries such as healthcare, finance, energy, and automation. As organizations increasingly rely on Data-driven decision-making, a strong understanding of machine learning fundamentals is essential for both students and professionals to remain relevant and effective in their roles.
This book provides a structured and intuitive learning experience through a Q&A format. It begins with foundational machine learning concepts, followed by detailed coverage of supervised and unsupervised learning techniques. The book explores key algorithms such as logistic regression, support vector machines (SVM), decision trees, and ensemble methods. It then progresses to advanced topics, including neural networks, dimensionality reduction, and modern trends like large language models (LLMs). Dedicated chapters on practical implementation using Python libraries, real-world applications, and interview-focused questions ensure a well-rounded understanding of both theory and practice.
By the end of this book, readers will have developed strong conceptual clarity and practical insight into machine learning techniques. They will be equipped to apply these concepts in real-world scenarios, approach problems with confidence, and perform effectively in academic, research, or industry roles. What you will learn
Learn supervised and unsupervised learning techniques with clarity.
Apply dimensionality reduction techniques for efficient data analysis.
Gain insights into neural networks and deep learning fundamentals.
Work with Python libraries for practical machine learning implementation.
Prepare effectively for interviews with structured Q&A practice. Who this book is for
This book is primarily intended for undergraduate students pursuing B.Tech, MCA, and related programs in computer science, artificial intelligence, and data science, as well as postgraduate students aiming to build strong fundamentals. It is also suitable for aspiring data scientists, machine learning engineers, and software professionals seeking conceptual clarity and practical understanding. Table of Contents
1. Basics of Machine Learning
2. Foundation of Supervised Machine Learning
3. Advanced Supervised Machine Learning
4. Ensemble Learning Techniques
5. Foundations of Unsupervised Learning
6. Unsupervised Machine Learning Algorithms
7. Dimensionality Reduction
8. Neural Networks
9. Sequential Models
10. Working with Python ML Libraries
11. Recent Trends in Machine Learning
12. Interview Questions and Concept Checks
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Wybrane elementy graficzne tej sekcji powstały przy wsparciu AI
Szczegóły książki
- ISBN Ebooka:
- 978-93-785-4454-5, 9789378544545
- Data wydania ebooka :
-
2026-09-23
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- Język publikacji:
- angielski
- Rozmiar pliku ePub:
- 16.3MB
- Rozmiar pliku Mobi:
- 16.3MB
- Zgłoś erratę
- Kategorie:
Dane » Data science » Deep Learning
Dane » Data science » Machine Learning
Programowanie » Języki programowania » Python
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