Showing results for "computer science" in Data Science

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

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.

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.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

A team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

Unlock the full potential of your data with the power of Python. Python for Data Science: A Practical Guide to Data Wrangling, Analysis, and Machine Learning Using Python’s Most Powerful Libraries is your comprehensive roadmap to mastering the tools and techniques that turn raw data into meaningful insights and predictive models.

While you may have never thought of networking in detail, this book will introduce you to the basics of networking, the different types of networks available, the types of network topologies that you will encounter, the concept of server virtualization, and details of how to handle network breaches.

The book Mastering AI Infrastructure and Cyber Security delves into the crucial aspects of safeguarding artificial intelligence (AI) systems and implementing robust infrastructure for AI applications. The book covers various topics, including AI algorithms, data privacy, cyber security threats, and defensive strategies.

In the rapidly evolving landscape of artificial intelligence and neuroscience, we stand at the precipice of a revolutionary understanding of how intelligence itself operates. The concept of "Data Cortex" represents more than just a metaphor—it embodies the fundamental principles that govern how information is processed, stored, and utilized in both biological and artificial systems. This audiobook explores the intricate relationships between the human brain's cortical structures and the data processing systems we create.

Curious about AI but unsure where to start? AI for Beginners Made Simple breaks down complex concepts into clear, practical insights—no tech background required! Discover how AI can enhance your career, automate tasks, and open new opportunities with easy-to-follow explanations, real-world applications, and hands-on projects. Learn AI basics, navigate ethical concerns, and access free resources—all without the jargon overload.

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.

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.

This is a two book bundle related to starting to master Python programming language and dominating the Linux operating system!

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 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.

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.

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.

Machine learning is a use of artificial intelligence (AI) that gives software the capacity to naturally learn and improve without being unequivocally modified. Machine learning centers around the improvement of computer programs that can get to data and use it to learn for themselves. The way toward learning starts with perceptions or data - for example, models, direct understanding, or guidance, so as to search for designs in data and settle on better choices later, depending on the models that we give.

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.