This audiobook is narrated by a digital voice.
"Mastering Data Science: Comprehensive Practice Questions for Certification" is an indispensable resource designed to aid aspiring data scientists in their journey towards certification. This book offers a thorough examination of key concepts and techniques essential for success in the field of data science.
Spanning topics such as Q Learning, Feature Selection, R, Python, TensorFlow, Feature Engineering, and Text Mining, each chapter provides a focused exploration of fundamental principles alongside practical applications. Through a series of meticulously crafted practice questions, readers are challenged to deepen their understanding and refine their problem-solving skills.
The section on Q Learning delves into reinforcement learning, elucidating the intricacies of this powerful technique and its applications in dynamic decision-making scenarios. Feature Selection is explored in depth, guiding readers through the process of identifying and extracting relevant features to enhance model performance.
Readers will navigate the landscapes of R and Python, two of the most widely used programming languages in data science, mastering data manipulation, visualization, and machine learning model development. The exploration of TensorFlow offers insights into deep learning frameworks, empowering readers to build and deploy sophisticated neural networks.
This audiobook is narrated by a digital voice.
"Mastering Data Science: Comprehensive Practice Questions for Certification" is an indispensable resource designed to aid aspiring data scientists in their journey towards certification. This book offers a thorough examination of key concepts and techniques essential for success in the field of data science.
Spanning topics such as Q Learning, Feature Selection, R, Python, TensorFlow, Feature Engineering, and Text Mining, each chapter provides a focused exploration of fundamental principles alongside practical applications. Through a series of meticulously crafted practice questions, readers are challenged to deepen their understanding and refine their problem-solving skills.
The section on Q Learning delves into reinforcement learning, elucidating the intricacies of this powerful technique and its applications in dynamic decision-making scenarios. Feature Selection is explored in depth, guiding readers through the process of identifying and extracting relevant features to enhance model performance.
Readers will navigate the landscapes of R and Python, two of the most widely used programming languages in data science, mastering data manipulation, visualization, and machine learning model development. The exploration of TensorFlow offers insights into deep learning frameworks, empowering readers to build and deploy sophisticated neural networks.
Product Details
BN ID: | 2940191283500 |
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Publisher: | Anand Vemula |
Publication date: | 09/05/2024 |
Edition description: | Unabridged |
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