Showing results for "Science" in Data Science

xGenius explores the interplay between analysis, tactics, and decision-making. It seeks to put the sport of football under the microscope with the aim of getting closer to the ultimate truth of what makes players, managers and teams successful. What, ultimately, wins football matches. Packed with examples from the Premier League and beyond, xGenius shows how xG and other performance analysis tools are helping answer previously unanswerable questions.

How to Build an Agent is not a book about experimenting with AI. It is a practical playbook for leaders who need AI systems that work in the real world. Most organisations use generative AI. Few see meaningful business results. This book explains why. Written for executives, senior managers, consultants, and technical leaders, it shows how to move beyond chatbots and prompts to autonomous, outcome-driven AI systems that plan, act, integrate with enterprise software, and deliver measurable ROI.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Data Science stands at the forefront of innovation in the tech industry, driving profound decisions and revolutionizing the way companies operate. "Ace the Data Science Interview" is your definitive guide to mastering the interview process at the most prestigious tech firms around the globe.

This book consists of 6 titles, namely: Assembly Language: The Ultimate Guide to Programming and Virtual Machines. Computer Science: The Complete Guide to Principles and Informatics. Cyber Security: Beginners’ Guide to Hacking, Phishing, Social Engineering, and Malware. Databases: System Concepts, Designs, Management, and Implementation. Operating Systems: Concepts to Save Money, Time, and Frustration. Website Development: Web Design Skills for Beginners

Did you know the value of data usage has increased job opportunities but that there are few specialists? These days, everyone is aware of the role data can play, whether it is an election, business, or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype? This audiobook presents you with a step-by-step approach to data science as well as secrets only known by the best data scientists.

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first audiobook of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond.

Data science is one of the most popular, lucrative and highly desirable skill set out there. Learning it—and mastering the craft—is a walk in the park when you have the right guidance.

In this clear, practical, and beginner-friendly audiobook, bestselling author Maxen Ford demystifies the world of data and shows you how to build real skills that matter in today’s job market. Data Science for Non-Techies is designed for professionals, students, and career-changers who want to understand how data drives decisions—without needing to code or memorize complex formulas.

In this book, you’ll find methods and techniques to organize your data, extract the information, and analyze it. There’s a way to make sure your company is going in the right direction, and this audiobook will reveal the secret behind a successful business.

Data science is the application of a combination of mathematical, statistical, analytical, and programming skills for the collection, organization, and interpretation of data to allow effective and proper management of the business whose data it is. The job of such a scientist is trending all over the world. The demand for such scientists is huge, more than the number of available candidates. Data science is a field of study that is growing at a fast pace. From big tech companies to E-commerce companies to websites and many others are now relying on data science.

In our highly competitive world of today, we need all the edge we can to get ahead of our competitors. For a long time, companies have focused on spending more on marketing and advertisement, ignoring the powerful asset they had at their disposal: data. Although this isn't the case anymore for large companies, smaller businesses are still in the dark about this, and you can use this asset to your advantage. This bundle will show you how.

Data science is an exciting field and will remain as such for many years to come. With more people than ever studying data science, machine learning & AI, there is an increasing gap between what you learn in the classroom and how data science is done in the real world. Inspired by conversations with nearly 10,000 social media followers, this book aims to close that gap and address some of the common tasks that you will face in your first year as a data scientist.

Un científico de datos es alguien que sabe más de informática que un estadístico, y conoce más estadísticas que un científico de la computación. Si bien, en gran medida, esto es cierto, convertirse en un buen científico de datos requiere el dominio no solo de estas dos áreas clave, sino también de algunas teorías y modelos cruciales para este campo. El libro se recomienda a todos los lectores interesados ​​que aspiran a destacarse en el campo de la ciencia de datos.

Descubra métodos y estrategias avanzadas para aprender ciencia de datos paraempresas. Las oportunidades que ofrece el big data son enormes; deje que este libro le ayude a aprovechar esas oportunidades. Ahora es el momento de comenzar a recopilar información esencial, hacer predicciones racionales y obtener una ventaja competitiva sobre otras empresas utilizando la amplia gama de datos disponibles en línea.

Computer science is a field that deals with the study of computers and computational systems. It encompasses both the theoretical and practical aspects of computing, including algorithms, data structures, programming languages, software engineering, and more. It's about understanding how computers work, how they can solve problems, and how they interact with humans and other systems.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.

Lars Nielsen and Noreen Burlingame provide a brief, understandable, user-friendly guide to all aspects of Data Science. The authors address the various skills required, the key steps in the Data Science process, software technology related to the effective practice of Data Science, and the best rising academic programs for training in the field.

Simply put, Dark Data is stored, largely non-inventoried, unstructured data not currently used for the purpose of conducting data science, but which is nevertheless maintained on a "just in case" basis - either to meet regulatory requirements, or in the hope that the data will prove useful for research purposes at some time in the future.

El objetivo de Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Machine Learning es ayudarle a expandir sus habilidades de ser un científico de datos básico a convertirse en un científico de datos experto listo para resolver problemas centrados en datos del mundo real. Al final de este libro, aprenderá cómo combinar Aprendizaje automático, Minería de datos, análisis y programación, y extraer conocimiento real de los datos.