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Description
Practical Handbook of Machine Learning | For Beginners, College Students & Software Professionals | No Coding or Advanced Math Required | Step-by-Step Guide with Python Basics, Hands-On Exercises, Real-World Applications & Video SupportUnlock the world of Machine Learning without needing any prior coding or advanced math knowledge with this step by step guide. Crafted for absolute beginners, this practical handbook by Subhrajit Bhattacharyya & Sujit Bhattacharyya is your entry point into the field. It makes complex concepts accessible through hands on exercises and real world applications. The book teaches you the necessary Python and math essentials from scratch and provides
Unlock the world of Machine Learning without needing any prior coding or advanced math knowledge with this step-by-step guide. Crafted for absolute beginners, this practical handbook by Subhrajit Bhattacharyya & Sujit Bhattacharyya is your entry point into the field. It makes complex concepts accessible through hands-on exercises and real-world applications.
The book teaches you the necessary Python and math essentials from scratch and provides additional support via QR-based video lessons and online MCQs. It’s the perfect resource for college students, software professionals, and curious learners alike.
Key Features:
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Beginner-Friendly Approach: A comprehensive guide crafted for those with zero coding or advanced math background, making machine learning accessible to all.
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Practical, Hands-On Learning: Features hands-on exercises and real-world applications to ensure concepts stick and prepare you for practical use.
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Essential Python & Math Basics: Teaches the fundamental Python and math essentials from scratch, so you don't need any prior knowledge.
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Multi-Format Support: Includes QR-based video lessons and online MCQs for self-testing, offering a modern, supported learning experience.
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Broad Audience Appeal: Tailored for a wide audience, including college students, faculty, software professionals, and anyone curious about the field.
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