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Build A Career In Data Science

Build a Career in Data Science PDF

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Author: Emily Robinson
Publisher: Manning Publications
ISBN: 1617296244
Size: 41.59 MB
Format: PDF
Category : Computers
Languages : en
Pages : 354
View: 742

Book Description: Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder


Data Science From Scratch

Data Science from Scratch PDF

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Author: Steven Cooper
Publisher: Roland Bind
ISBN:
Size: 43.95 MB
Format: PDF
Category : Computers
Languages : en
Pages : 156
View: 5161

Book Description: ★☆If you are looking to start a new career that is in high demand, then you need to continue reading!★☆​​​​​​​ Data scientists are changing the way big data is used in different institutions. Big data is everywhere, but without the right person to interpret it, it means nothing. So where do business find these people to help change their business? You could be that person! It has become a universal truth that businesses are full of data. With the use of big data, the US healthcare could reduce their health-care spending by $300 billion to $450 billion. It can easily be seen that the value of big data lies in the analysis and processing of that data, and that's where data science comes in. ★★ Grab your copy today and learn ★★ ♦ In depth information about what data science is and why it is important. ♦ The prerequisites you will need to get started in data science. ♦ What it means to be a data scientist. ♦ The roles that hacking and coding play in data science. ♦ The different coding languages that can be used in data science. ♦ Why python is so important. ♦ How to use linear algebra and statistics. ♦ The different applications for data science. ♦ How to work with the data through munging and cleaning ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. As businesses and the internet change, so will data science. This means it's important to be flexible. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started in a new, ever growing, career, don't wait any longer. Scroll up and click the buy now button to get this book today!


Practical Data Science With Sap

Practical Data Science with SAP PDF

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Author: Greg Foss
Publisher: O'Reilly Media
ISBN: 1492046418
Size: 50.43 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 332
View: 6364

Book Description: Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths. You'll explore: Examples of how data analysis can help you solve several SAP challenges Natural language processing for unlocking the secrets in text Data science techniques for data clustering and segmentation Methods for detecting anomalies in your SAP data Data visualization techniques for making your data come to life


97 Things About Ethics Everyone In Data Science Should Know

97 Things About Ethics Everyone in Data Science Should Know PDF

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Author: Bill Franks
Publisher: O'Reilly Media
ISBN: 149207263X
Size: 22.53 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 346
View: 1025

Book Description: Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics simply aren’t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Concept—Tim Wilson How to Approach Ethical Transparency—Rado Kotorov Unbiased ≠ Fair—Doug Hague Rules and Rationality—Christof Wolf Brenner The Truth About AI Bias—Cassie Kozyrkov Cautionary Ethics Tales—Sherrill Hayes Fairness in the Age of Algorithms—Anna Jacobson The Ethical Data Storyteller—Brent Dykes Introducing Ethicize™, the Fully AI-Driven Cloud-Based Ethics Solution!—Brian O’Neill Be Careful with "Decisions of the Heart"—Hugh Watson Understanding Passive Versus Proactive Ethics—Bill Schmarzo


30 Second Data Science

30 Second Data Science PDF

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Author: Liberty Vittert
Publisher: 30 Second
ISBN: 0711259666
Size: 40.59 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 160
View: 217

Book Description: 30-Second Data Science is the quickest way to discover how data is a driving force not just in the big issues, such as climate change and healthcare, but in our daily lives. Data science is an entirely new discipline that encompasses a new era of information, from finding criminals to predicting epidemics. But there's more to it than the vast quantities of information gathered by our computers, smartphones, and credit cards. Carefully compiled by experts in the field, 30-Second Data Science covers the basic statistical principles that drive the algorithms, how data affects us in every way--science, society, business, pleasure--along with the ethical quandaries and its future promise of a better world. Each 30-Second entry details a different facet of data science in just 300 words and one picture, showing how the concept of bringing together different types of data, and using powerful computer programs to find patterns no human eye could spot, is already transforming our world. Exploring key ideas and featuring biographies of the people behind them, 30-Second Data Science explains clearly and concisely all you need to know about data science, from basics to ethics.


Data Science And Big Data Computing

Data Science and Big Data Computing PDF

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Author: Zaigham Mahmood
Publisher: Springer
ISBN: 9783319811390
Size: 26.60 MB
Format: PDF
Category : Business & Economics
Languages : en
Pages : 319
View: 1974

Book Description: This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.


Data Science

                                                                              Data Science PDF

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Author: Брюс П.
Publisher: БХВ-Петербург
ISBN: 5977539746
Size: 42.37 MB
Format: PDF, ePub
Category :
Languages : ru
Pages : 304
View: 2928

Book Description: Книга рассчитана на специалистов в области Data Science, обладающих некоторым опытом работы с языком программирования R и имеющих предварительное понятие о математической статистике. В ней в удобной и легкодоступной форме представлены ключевые понятия из статистики, которые относятся к науке о данных, а также объяснено, какие понятия важны и полезны с точки зрения науки о данных, какие менее важны и почему. Подробно раскрыты темы: разведочный анализ данных, распределения данных и выборок, статистические эксперименты и проверка значимости, регрессия и предсказание, классификация, статистическое машинное обучение и обучение без учителя. "...Эта книга не является ни очередным учебником по статистике, ни руководством по машин-ному обучению. Она гораздо лучше, поскольку наглядно показывает связь между полезными статистическими терминами и принципами, с одной стороны, и сегодняшними малопонят-ными жаргонизмами и методами глубинного анализа данных, с другой, давая ясные объясне-ния и большое количество примеров. Это потрясающий справочник для новичков и специа-листов науки о данных...". - Галит Шмуели Автор популярной серии Глубинный анализ данных для деловой аналитики (Data Mining for Business Analytics) и почетный профессор национального университета Циньхуа, Тайвань


Data Science From Scratch

Data Science from Scratch PDF

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Author: O'Reilly
Publisher: БХВ-Петербург
ISBN: 5977537581
Size: 46.11 MB
Format: PDF, ePub, Mobi
Category :
Languages : ru
Pages : 336
View: 4554

Book Description: Книга позволяет изучить науку о данных (Data Science) и применить полученные знания на практике. Она написана так, что способствуют погружению в Data Science анали-тика, фактически не обладающего глубокими знаниями в этой прикладной дисцип-лине. В объемах, достаточных для начала работы в области Data Science, книга содержит интенсивный курс языка Python, элементы линейной алгебры, математической ста-тистики, теории вероятностей, методов сбора, очистки, нормализации и обработки данных. Даны основы машинного обучения. Описаны различные математические модели и их реализация по методу k-ближайших соседей, наивной байесовской клас-сификации, линейной и логистической регрессии, а также модели на основе деревьев принятия решений, нейронных сетей и кластеризации. Рассказано о работе с реко-мендательными системами, описаны приемы обработки естественного языка, методы анализа социальных сетей, основы баз данных, SQL и MapReduce.


Data Science

Data Science                       PDF

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Author: Том Фоусет
Publisher: Наш формат
ISBN: 6177730043
Size: 19.27 MB
Format: PDF, ePub
Category : Computers
Languages : uk
Pages : 400
View: 4059

Book Description: Протягом останніх років не лише технологічні гіганти, а й інші компанії навчилися збирати дані про операційну роботу, результати маркетингових кампаній і поведінку своїх клієнтів. Проте не всі вміють застосовувати їх на користь власній справі. Потрібно мислити, як Data Science-фахівець, щоб приймати бізнес-рішення на основі даних, стверджують автори цієї книги.


Data Science Workflow For Beginners

Data Science Workflow for Beginners PDF

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Author: Alejandro Garcia
Publisher: Alejandro Garcia
ISBN:
Size: 33.96 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages :
View: 7514

Book Description: This book brings to you a simple yet effective 40 to 60 mins introduction that will clear all your doubts about Data Sience and will answer some important questions like: What is data Science ? The book explores all the initial concepts a person might want to know about the data science workflow. There’s not coding, math or statistics required to successfully understand the goals and end results of this process. This book takes you on an exclusive tour of datasets and sites to download your first datasets. Then jumps into a comprehensive and easy-to-follow data science process letting you go through 3 data visualization projects. (Python Code Understanding is Recommended for the Data Visualization projects) - 40 to 60 mins reading time. - 3 Data Visualization projects. - 10 Datasets sources. - 26 Quality datasets for your first visualizations. - Get the code and reuse in your own projects. The ebook covers: - Intro to Data Science. - The Workflow of Data Science. - Data Science and Machine Learning. - Datasets to start right away. - Data Visualization Projects. (Python Code Understanding Recommended)


Python For Data Science For Dummies

Python for Data Science For Dummies PDF

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Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 1119547628
Size: 40.43 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 496
View: 2930

Book Description: The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and Python Visualize information Wrangle data Learn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.