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Key benefits

Master the concepts of statistics and ML to interpret models and guide decisions

Identify valuable AI use cases and manage data science projects from start to finish

Empower top data science teams to solve complex problems and build AI products

Purchase of the print Kindle book includes a free PDF eBook

Description

As data science and artificial intelligence (AI) become prevalent across industries, executives without formal education in statistics and machine learning, as well as data scientists moving into leadership roles, must learn how to make informed decisions about complex models and manage data teams. This book will elevate your leadership skills by guiding you through the core concepts of data science and AI. This comprehensive guide is designed to bridge the gap between business needs and technical solutions, empowering you to make informed decisions and drive measurable value within your organization. Through practical examples and clear explanations, you'll learn how to collect and analyze structured and unstructured data, build a strong foundation in statistics and machine learning, and evaluate models confidently. By recognizing common pitfalls and valuable use cases, you'll plan data science projects effectively, from the ground up to completion. Beyond technical aspects, this book provides tools to recruit top talent, manage high-performing teams, and stay up to date with industry advancements. By the end of this book, you’ll be able to characterize the data within your organization and frame business problems as data science problems.

Who is this book for?

This book is designed for executives who want to understand and apply data science methods to enhance decision-making. It is also for individuals who work with or manage data scientists and machine learning engineers, such as chief data officers (CDOs), data science managers, and technical project managers.

What you will learn

Discover how to interpret common statistical quantities and make data-driven decisions

Explore ML concepts as well as techniques in supervised, unsupervised, and reinforcement learning

Find out how to evaluate statistical and machine learning models

Understand the data science lifecycle, from development to monitoring of models in production

Know when to use ML, statistical modeling, or traditional BI methods

Manage data teams and data science projects effectively

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

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Total ₹ 9,682.97

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What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

Steven Fernandes Aug 06, 2024

The book provides a clear and practical overview of key concepts in data science and machine learning. The book begins with a foundational understanding of how to interpret common statistical measures and make informed decisions based on data. It then covers a range of machine learning methodologies, including supervised, unsupervised, and reinforcement learning. Readers will learn how to evaluate both statistical and machine learning models effectively and understand the full data science lifecycle, from development to deployment. The guide also offers insights into choosing between ML, statistical modeling, and traditional BI methods and includes valuable advice on managing data teams and projects. A great resource for aspiring data scientists and analytics managers.

Amazon Verified review

Sai Kumar Bysani Oct 15, 2024

𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐦𝐲 𝐤𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬:1. 𝐂𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧: The book introduces key data science concepts like exploratory data analysis (EDA) and feature engineering. It simplifies understanding of these critical steps in any machine learning pipeline.2. 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: From regression to clustering, the book breaks down both supervised and unsupervised learning algorithms. It also covers important aspects like hyperparameter tuning and model optimization.3. 𝐀𝐯𝐨𝐢𝐝𝐢𝐧𝐠 𝐂𝐨𝐦𝐦𝐨𝐧 𝐏𝐢𝐭𝐟𝐚𝐥𝐥𝐬: The book highlights key pitfalls such as overfitting, bias, and issues related to data quality. By addressing challenges like model generalization and data consistency, it ensures that machine learning models are robust and reliable.4. 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥𝐬: The book provides detailed guidance on evaluating models using metrics like accuracy, precision, recall, and AUC-ROC curves. It also explains how to interpret these results to make informed decisions.5. 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: It covers essential statistical concepts such as hypothesis testing, p-values, and confidence intervals. These are critical for making data-driven decisions and evaluating models.6. 𝐕𝐢𝐬𝐮𝐚𝐥𝐥𝐲 𝐄𝐧𝐠𝐚𝐠𝐢𝐧𝐠 𝐏𝐢𝐜𝐭𝐮𝐫𝐞𝐬: The book uses clear visuals like charts, graphs, and confusion matrices to break down complex topics. These images make it easier to understand the material and apply it practically.Additionally, the book includes practical case studies such as fraud detection, churn prediction, forecasting, and many more. These real-world examples help illustrate how data science techniques are applied to solve complex business problems. I had a great time reading this book!

Om S Aug 07, 2024

Stepping into a leadership role, "Data Science for Decision Makers" guided me through the complexities of data science and AI. It covers everything from collecting and analyzing data to understanding machine learning concepts. With practical examples, I learned to interpret models and make informed decisions. The book also provides tools for managing data science projects and teams, making it an invaluable resource for executives looking to leverage data for impactful results.

Kog Aug 30, 2024

This has something for everyone from Data Science world—whether you're an executive, a manager, a consultant, an AI expert, a Data scientist, a researcher or just someone curious about how data can shape business strategy and strategic decisions! 📚#DataScience #DecisionMaking #BusinessStrategy #Leadership #ContinuousLearning

Amazon Customer Sep 10, 2024

This book excels in its mission to elevate leadership skills by demystifying the core concepts of data science and AI. It offers a clear and practical guide for understanding and utilizing data to drive business value. The author break down intricate topics into accessible explanations, making complex concepts like statistical quantities, machine learning techniques, and model evaluation comprehensible for those without a deep technical background.The book equips leaders with the tools to make informed decisions about when to deploy ML, statistical models, or traditional business intelligence methods.In summary, this book is an invaluable resource for executives and emerging leaders in data science.It provides a thorough grounding in essential data science concepts while offering actionable insights and practical strategies for applying this knowledge in a business context.

Data Science for Decision Makers: Enhance your leadership skills with data science and AI expertise

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