Who is the target audience for this book?

This book is designed for a diverse audience ranging from students, professionals in data science, to hobbyists interested in machine learning. It caters to both newcomers who want a thorough grounding in the basics as well as those with coding experience looking to implement machine learning algorithms from scratch. Readers will find it beneficial, especially if they appreciate a hands-on approach combined with theoretical knowledge.

What programming languages are used in the book?

The book predominantly uses Python for coding examples, as it is one of the most popular languages for machine learning and data analysis. Moreover, it combines mathematical explanations with practical coding to enhance understanding. By using Python, readers can easily follow along and implement algorithms due to its clear syntax and extensive libraries like NumPy and Pandas.

Can this book help with practical machine learning applications?

Absolutely! The book provides practical machine learning applications through its coding examples, allowing readers to implement algorithms in real-world scenarios. By building models from scratch, readers gain hands-on experience with essential techniques like regression, classification, and clustering, which they can apply in fields such as finance, healthcare, marketing, and more.

Does the book require any prior knowledge of machine learning or programming?

No prior knowledge of machine learning or programming is strictly necessary to benefit from this book. It starts with the fundamental concepts and gradually progresses to more complex topics. However, a basic understanding of programming concepts, particularly in Python, will enhance the learning experience. The author takes a pedagogical approach, making it accessible to eager learners at all levels.

What are some key machine learning algorithms covered in the book?

The book covers a wide range of machine learning algorithms, including linear regression, logistic regression, decision trees, support vector machines, and neural networks. Each chapter dives deep into the specific algorithm, discussing its mathematical foundations, implementation in code, and practical applications, thus providing a holistic view of machine learning techniques.

How does this book differ from other machine learning resources?

Unlike many resources that rely heavily on higher-level libraries, this book emphasizes building algorithms from the ground up. This approach fosters a deeper understanding of the inner workings and mechanics of machine learning models. Readers appreciate how it combines theory with coding tasks, empowering them to grasp complex concepts beyond surface-level application.

Is there a focus on mathematical concepts in the book?

Yes, the book places significant emphasis on the mathematical concepts underlying machine learning algorithms. It explains essential math topics such as linear algebra, calculus, and probability in an intuitive manner while integrating them into practical coding scenarios. This focus equips readers with the necessary theoretical tools to comprehend the algorithms they are implementing.

What kind of projects can I build after reading this book?

After completing the book, readers can embark on various real-world projects, such as developing predictive models for sales forecasting, building recommendation systems, or analyzing social media sentiment. These projects enhance programming skills and deepen understanding of machine learning concepts and their applications across different industries, making readers more marketable in the tech space.

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Machine Learning From Scratch: Intuition, Math and Code of ML Algorithms

By the end of this book, the black box will be completely gone. You will walk away with a complete, repeatable workflow and a genuine understanding of exactly what's happening inside every model you build.

Item #: 248065679

Machine Learning From Scratch: Intuition, Math and Code of ML Algorithms

Q: What is Machine Learning From Scratch Intuition, Math And Code Of ML Algorithms about?

The book, 'Machine Learning From Scratch Intuition, Math And Code Of ML Algorithms,' serves as a comprehensive introduction to the fundamental principles of machine learning. It covers the theoretical foundations, mathematical underpinnings, and practical coding implementations of various algorithms. Whether you're a beginner looking to understand core concepts or an experienced programmer seeking to deepen your knowledge, this book offers invaluable insights and hands-on coding examples using popular programming languages.

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What Stands Out

Comprehensive Coverage

Offers in-depth insights into machine learning concepts, ensuring a thorough understanding of both intuition and mathematics behind algorithms, making it suitable for beginners and advanced learners alike.

Hands-On Coding

Includes practical coding examples that allow users to implement algorithms from scratch, bridging the gap between theory and practice for an engaging learning experience.

Accessible Approach

Designed to simplify complex topics, this resource uses relatable explanations and visual aids, enabling readers to grasp challenging concepts more effectively than traditional learning materials.

Product Details

Publisher	Oleksandr Akimenko
Publication date	May 27, 2026
Language	English
Print length	316 pages
ISBN-10	106751970X
ISBN-13	978-1067519704
Item Weight	15 ounces (425.25 grams)
Dimensions	6 x 0.72 x 9 inches (15.2 x 1.8 x 22.9 cm)

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Aspiring Data Scientists
Ideal for beginners looking to gain a solid understanding of machine learning concepts and algorithms step-by-step.
Self-Learners
Perfect for individuals wanting to teach themselves machine learning in a structured way with practical coding examples.
Developers Transitioning
Great for software developers shifting towards artificial intelligence who need foundational knowledge in machine learning.

Advanced Practitioners
Not suitable for experienced machine learning professionals seeking advanced algorithms or cutting-edge research topics.

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Machine Learning From Scratch: Intuition, Math and Code of ML Algorithms

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Question: How Long Does It Take to Get Product After Placing the Order?

Answer: The delivery time of your ordered product varies as per what you've ordered and the shipping method that you've chosen. The estimated delivery time is mentioned during the checkout process, so be carefree while shopping.

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Features & Benefits

Transform from a beginner to an ML practitioner with basic Python and math.
Build 10 core ML algorithms from scratch, including Neural Networks and XGBoost.
Learn to apply industry standards like Scikit-learn and PyTorch.
Optimize your models with hyperparameter tuning using Optuna.
Access practical examples and ready-to-run notebooks for hands-on learning.
Gain a deep understanding of the workings behind each model you create.

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Machine Learning From Scratch: Intuition, Math and Code of ML Algorithms

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