Mastering Data Science: Comprehensive Practice Questions for Certification -Computational Graph, Banyan Tree, Colloborative Filtering, Random Forest,Cosine Distance, Binary Tree

Anand Vemula ยท แƒฎแƒ”แƒšแƒแƒ•แƒœแƒฃแƒ แƒ˜ แƒ˜แƒœแƒขแƒ”แƒšแƒ”แƒฅแƒขแƒ˜แƒก แƒ›แƒ˜แƒ”แƒ  แƒ›แƒแƒ—แƒฎแƒ แƒแƒ‘แƒ˜แƒšแƒ˜ Madison-แƒ˜แƒกแƒ’แƒแƒœ (Google-แƒ˜แƒ“แƒแƒœ)
แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ˜
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แƒ แƒ”แƒ˜แƒขแƒ˜แƒœแƒ’แƒ”แƒ‘แƒ˜ แƒ“แƒ แƒ›แƒ˜แƒ›แƒแƒฎแƒ˜แƒšแƒ•แƒ”แƒ‘แƒ˜ แƒ“แƒแƒฃแƒ“แƒแƒกแƒขแƒฃแƒ แƒ”แƒ‘แƒ”แƒšแƒ˜แƒ ย แƒจแƒ”แƒ˜แƒขแƒงแƒ•แƒ”แƒ— แƒ›แƒ”แƒขแƒ˜

แƒแƒ› แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ˜แƒก แƒจแƒ”แƒกแƒแƒฎแƒ”แƒ‘

Mastering Data Science: Comprehensive Practice Questions for Certification" is a comprehensive guide designed to help aspiring data scientists prepare for certification exams. Authored by experts in the field, this book covers essential topics ranging from computational graphs to collaborative filtering, ensuring a thorough understanding of key concepts.


The book begins by delving into computational graphs, providing detailed explanations and practice questions to reinforce learning. Readers learn how to construct and manipulate computational graphs, essential for understanding various machine learning algorithms.


Next, the book explores the intricacies of the Banyan Tree algorithm, offering insights into its structure, operations, and applications in data science tasks. With practical examples and exercises, readers can master this powerful algorithm and its implementations.


Collaborative filtering, another crucial aspect of data science, is thoroughly covered, with a focus on recommendation systems and user-item interactions. Readers gain a deep understanding of collaborative filtering techniques and their significance in personalized recommendation systems.


Random Forest, a widely used ensemble learning method, is extensively discussed, with practice questions to solidify comprehension. Readers learn how Random Forest algorithms work, their advantages, and how to effectively implement them in various scenarios.


Cosine distance, a fundamental concept in similarity measurement, is explored in detail, along with its applications in text mining, recommendation systems, and clustering algorithms.


Lastly, the book covers binary trees, providing insights into their structure, traversal methods, and applications in data science. With comprehensive practice questions accompanying each topic, readers can assess their understanding and readiness for certification exams.


Overall, "Mastering Data Science: Comprehensive Practice Questions for Certification" serves as an invaluable resource for aspiring data scientists, offering a thorough coverage of essential topics and ample opportunities for practice and self-assessment.

แƒแƒ•แƒขแƒแƒ แƒ˜แƒก แƒจแƒ”แƒกแƒแƒฎแƒ”แƒ‘

Technology Evangelist with 27 years of experience in Digital Technology

แƒแƒ› แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ˜แƒก แƒจแƒ”แƒคแƒแƒกแƒ”แƒ‘แƒ

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แƒ“แƒแƒแƒ˜แƒœแƒกแƒขแƒแƒšแƒ˜แƒ แƒ”แƒ— Google Play Books แƒแƒžแƒ˜ Android แƒ“แƒ iPad/iPhone แƒ›แƒแƒฌแƒงแƒแƒ‘แƒ˜แƒšแƒแƒ‘แƒ”แƒ‘แƒ˜แƒกแƒ—แƒ•แƒ˜แƒก. แƒ˜แƒก แƒแƒ•แƒขแƒแƒ›แƒแƒขแƒฃแƒ แƒแƒ“ แƒ’แƒแƒœแƒแƒฎแƒแƒ แƒชแƒ˜แƒ”แƒšแƒ”แƒ‘แƒก แƒกแƒ˜แƒœแƒฅแƒ แƒแƒœแƒ˜แƒ–แƒแƒชแƒ˜แƒแƒก แƒ—แƒฅแƒ•แƒ”แƒœแƒก แƒแƒœแƒ’แƒแƒ แƒ˜แƒจแƒ—แƒแƒœ แƒ“แƒ แƒกแƒแƒจแƒฃแƒแƒšแƒ”แƒ‘แƒแƒก แƒ›แƒแƒ’แƒชแƒ”แƒ›แƒ—, แƒฌแƒแƒ˜แƒ™แƒ˜แƒ—แƒฎแƒแƒ— แƒกแƒแƒกแƒฃแƒ แƒ•แƒ”แƒšแƒ˜ แƒ™แƒแƒœแƒขแƒ”แƒœแƒขแƒ˜ แƒœแƒ”แƒ‘แƒ˜แƒกแƒ›แƒ˜แƒ”แƒ  แƒแƒ“แƒ’แƒ˜แƒšแƒแƒก, แƒ แƒแƒ’แƒแƒ แƒช แƒแƒœแƒšแƒแƒ˜แƒœ, แƒ˜แƒกแƒ” แƒฎแƒแƒ–แƒ’แƒแƒ แƒ”แƒจแƒ” แƒ แƒ”แƒŸแƒ˜แƒ›แƒจแƒ˜.
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แƒจแƒ”แƒ’แƒ˜แƒซแƒšแƒ˜แƒแƒ— แƒฌแƒแƒ˜แƒ™แƒ˜แƒ—แƒฎแƒแƒ— Google Play-แƒ–แƒ” แƒจแƒ”แƒซแƒ”แƒœแƒ˜แƒšแƒ˜ แƒฌแƒ˜แƒ’แƒœแƒ”แƒ‘แƒ˜ แƒ—แƒฅแƒ•แƒ”แƒœแƒ˜ แƒ™แƒแƒ›แƒžแƒ˜แƒฃแƒขแƒ”แƒ แƒ˜แƒก แƒ•แƒ”แƒ‘ แƒ‘แƒ แƒแƒฃแƒ–แƒ”แƒ แƒ˜แƒก แƒ’แƒแƒ›แƒแƒงแƒ”แƒœแƒ”แƒ‘แƒ˜แƒ—.

แƒ›แƒ”แƒขแƒ˜ แƒแƒ•แƒขแƒแƒ แƒ˜แƒกแƒ’แƒแƒœ Anand Vemula

แƒ›แƒกแƒ’แƒแƒ•แƒกแƒ˜ แƒแƒฃแƒ“แƒ˜แƒแƒฌแƒ˜แƒ’แƒœแƒ”แƒ‘แƒ˜

แƒ›แƒ—แƒฎแƒ แƒแƒ‘แƒ”แƒšแƒ˜ Madison-แƒ˜แƒก แƒ›แƒ˜แƒ”แƒ