Data Science: Experiment, Validate, Collaborate
Chopra, Shobha Srinivasan
ISBN 10: 3384209257 ISBN 13: 9783384209252
Published by Tredition Gmbh, 2024
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Data science isn't a one-shot game. Unlike traditional software development, it thrives on constant exploration. This is where experimentation reigns supreme. Forget rigid blueprints; data science projects are iterative journeys guided by the scientific method. We ask questions, form hypotheses, test them with diverse datasets, features, algorithms, and parameters. Analyzing results becomes a loop - success leads to refinement, and roadblocks spark new experiments. This focus on experimentation creates a unique validation process. Unlike software's binary "works or doesn't," data science thrives in shades of gray. One model might be "good" for one person's needs, needing further exploration for another's. Here, clear communication and collaboration are crucial. Tools like version control not only for code, but also for data and models, ensure everyone's on the same page. Experiment tracking becomes vital, documenting the "why" behind decisions and results. By embracing experimentation, data science unlocks a world of possibilities. It's not about finding the perfect answer, but continuously improving through exploration and collaboration. This is the essence of the data science experiment - where the journey itself holds the key to groundbreaking discoveries
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Title: Data Science: Experiment, Validate, ...
Publisher: Tredition Gmbh
Publication Date: 2024
Binding: Soft cover
Condition: New
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Data Science: Experiment, Validate, Collaborate
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ISBN 10: 3384209257
ISBN 13: 9783384209252
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Taschenbuch. Condition: Neu. Neuware -Data science isn't a one-shot game. Unlike traditional software development, it thrives on constant exploration. This is where experimentation reigns supreme. Forget rigid blueprints; data science projects are iterative journeys guided by the scientific method. We ask questions, form hypotheses, test them with diverse datasets, features, algorithms, and parameters. Analyzing results becomes a loop ¿ success leads to refinement, and roadblocks spark new experiments.This focus on experimentation creates a unique validation process. Unlike software's binary 'works or doesn't,' data science thrives in shades of gray. One model might be 'good' for one person's needs, needing further exploration for another's. Here, clear communication and collaboration are crucial. Tools like version control not only for code, but also for data and models, ensure everyone's on the same page. Experiment tracking becomes vital, documenting the 'why' behind decisions and results.By embracing experimentation, data science unlocks a world of possibilities. It's not about finding the perfect answer, but continuously improving through exploration and collaboration. This is the essence of the data science experiment ¿ where the journey itself holds the key to groundbreaking discoveries 56 pp. Englisch. Seller Inventory # 9783384209252
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Data Science: Experiment, Validate, Collaborate
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Taschenbuch. Condition: Neu. Data Science: Experiment, Validate, Collaborate | Shobha Srinivasan Chopra | Taschenbuch | Englisch | 2024 | tredition | EAN 9783384209252 | Verantwortliche Person für die EU: tredition GmbH, Heinz-Beusen-Stieg 5, 22926 Ahrensburg, info[at]tredition[dot]de | Anbieter: preigu. Seller Inventory # 129014164
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Data Science: Experiment, Validate, Collaborate
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data science isn't a one-shot game. Unlike traditional software development, it thrives on constant exploration. This is where experimentation reigns supreme. Forget rigid blueprints; data science projects are iterative journeys guided by the scientific method. We ask questions, form hypotheses, test them with diverse datasets, features, algorithms, and parameters. Analyzing results becomes a loop - success leads to refinement, and roadblocks spark new experiments.This focus on experimentation creates a unique validation process. Unlike software's binary 'works or doesn't,' data science thrives in shades of gray. One model might be 'good' for one person's needs, needing further exploration for another's. Here, clear communication and collaboration are crucial. Tools like version control not only for code, but also for data and models, ensure everyone's on the same page. Experiment tracking becomes vital, documenting the 'why' behind decisions and results.By embracing experimentation, data science unlocks a world of possibilities. It's not about finding the perfect answer, but continuously improving through exploration and collaboration. This is the essence of the data science experiment - where the journey itself holds the key to groundbreaking discoveries. Seller Inventory # 9783384209252
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Data Science: Experiment, Validate, Collaborate
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Data science isn t a one-shot game. Unlike traditional software development, it thrives on constant exploration. This is where experimentation reigns supreme. Forget rigid blueprints data science projects are iterative journeys guided by the scientific met. Seller Inventory # 1596320194
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data science isn't a one-shot game. Unlike traditional software development, it thrives on constant exploration. This is where experimentation reigns supreme. Forget rigid blueprints; data science projects are iterative journeys guided by the scientific method. We ask questions, form hypotheses, test them with diverse datasets, features, algorithms, and parameters. Analyzing results becomes a loop - success leads to refinement, and roadblocks spark new experiments.This focus on experimentation creates a unique validation process. Unlike software's binary 'works or doesn't,' data science thrives in shades of gray. One model might be 'good' for one person's needs, needing further exploration for another's. Here, clear communication and collaboration are crucial. Tools like version control not only for code, but also for data and models, ensure everyone's on the same page. Experiment tracking becomes vital, documenting the 'why' behind decisions and results.By embracing experimentation, data science unlocks a world of possibilities. It's not about finding the perfect answer, but continuously improving through exploration and collaboration. This is the essence of the data science experiment - where the journey itself holds the key to groundbreaking discoveries 54 pp. Englisch. Seller Inventory # 9783384209252