Roshna S H

Dr. Roshna S H is a scientist by profession with more than five years of teaching experience at graduate and postgraduate levels. She has obtained a Ph.D. from IIT Madras after M.Sc., M. Phil in Physics. She has also cleared CSIR-NET and GATE with top ranks. She is a constant content creator through publications in peer-reviewed international journals and by writing concept based blog articles. She has research experiences in diverse areas spans from atmospheric science to optics as well as spintronics and magnetism. She has obtained awards and recognitions at various international platforms for her contributions as scientific articles and oral presentations. Dr. Roshna completed her Ph.D. with exposure at American physical society, Material research society, University of Oxford, etc. She focuses on communicating the concepts with utmost clarity in the simplest possible way.

Python Foundations-12: Hands-On with Advanced Techniques in Linear algebra for Machine Learning

Linear algebra serves as the cornerstone of numerous machine learning algorithms. In this article, we’ll explore six advanced concepts, providing not just explanations but hands-on with advanced techniques in linear algebra using Python code for each. Buckle up as we dive into these powerful linear algebra techniques that will elevate your machine learning skills. If …

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Python Foundations-11: Advanced Linear Algebra Concepts for Machine Learning

Welcome back to our ongoing exploration of Python foundations for machine learning! In our previous articles on linear algebra for machine learning, we delved into fundamental concepts like vector operations, matrix manipulations, and eigenvalues. In this installment, we will tackle more advanced linear algebra concepts to enhance your grasp of these crucial principles and further …

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Python Foundations-10: Mastering Linear Algebra for Machine Learning

Welcome back to the continuation of our exploration of Linear Algebra for Machine Learning! In the previous articles, we covered fundamental concepts such as vector addition/subtraction, matrix multiplication, matrix transpose, eigenvalues, singular value decomposition, linear equations and so on. Now, let’s dive into a set of new problems to reinforce and expand our understanding of …

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Python Foundations-9: Elevating Linear Algebra for Machine Learning

Welcome back to our ongoing journey through Python Foundations for Machine Learning! In the previous article, we explored the basics of Linear Algebra, focusing on vector addition, matrix multiplication, eigenvalues, singular value decomposition, and linear equations. In this article, we’ll continue our exploration with a set of new problems to further solidify your grasp of …

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Python Foundations-8: A Beginner’s Guide to Linear Algebra for Machine Learning with Python

If you’re just joining us for this article “A Beginner’s Guide to Linear Algebra for Machine Learning”, we recommend checking out the introduction in the previous article, which sets the stage for our exploration into the world of linear algebra and its applications in machine learning. Introduction: Linear algebra serves as the cornerstone for understanding …

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Python Foundations-7: Unlocking Linear Algebra for Machine Learning

Welcome to the exciting world of linear algebra for machine learning! If you’re stepping into this realm, you’ve likely heard the term “linear algebra” thrown around. In this series, we’re going to unravel the mysteries behind this mathematical powerhouse and explore its significance in the realm of machine learning. What is Linear Algebra? Linear algebra …

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sapiens

“Sapiens” by Yuval Noah Harari: Unveiling the Epic Tale of Humanity

“Sapiens” by Yuval Noah Harari is a literary masterpiece that takes readers on an enthralling journey through the annals of human history, unraveling the complex tapestry of our shared past. In this review, we will delve into the key themes and insights offered by Harari, exploring the book’s impact on our understanding of Homo sapiens …

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Python Foundations-6: Advanced Challenges in Probability and Statistics for Machine Learning

Welcome back to the next chapter of our “Python Foundations” series. Building upon the beginner-level problems in the previous articles, we are ready to explore more advanced challenges in probability and statistics tailored for machine learning enthusiasts. Problem 1: Conditional Probability Challenge Problem Statement: Calculate the conditional probability of event B given event A using …

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Python Foundations-5: Intermediate Probability and Statistics Challenges for Machine Learning

Welcome to the fifth chapter of our “Python Foundations” series, where we venture into the intricate domain of probability and statistics with a moderate level of difficulty. In this article, we present 5 new problems, say from intermediate-level probability and statistics, each accompanied by comprehensive theoretical explanations and practical Python code, designed to refine your …

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Python Foundations-4: Intermediate Probability and Statistics Challenges for Machine Learning Mastery

Welcome back to the “Python Foundations” series! In our previous articles, we explored beginner-level probability and statistics problems to build a strong foundation for machine learning. Now, let’s delve into intermediate level probability and statistics challenges for machine learning that will further enhance your skills in this crucial aspect of data science. Problem 1: Confidence …

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