AI-Assisted Statistics for Data Scientists, 3E by Peter Bruce (.ePUB)+
File Size: 22.7 MB
AI-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, 3rd Edition by Peter Bruce, Andrew Bruce, Peter Gedeck
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Overview: Statistical methods are a key part of Data Science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The third edition of this popular guide expands its practical foundations in R and Python into the modern AI toolkit, with new chapters on neural networks, deep learning, and large language models. Generative AI is integrated throughout, showing how tools such as ChatGPT, Claude, and Gemini work, and how they can support real-world statistical workflows. This book highlights concepts that matter most when working with data, building predictive models, and deploying AI responsibly. If you’re comfortable with R or Python and have had some exposure to basic statistics, this concise reference will boost your statistical literacy, your understanding of how AI works, and your confidence in real-world data science and AI projects. Data scientists, Machine Learning practitioners, and software engineers have come to know AI as a powerful coding tool. Vibe coding refers to the ability of AI models to produce code based on specifications (a prompt) written in English or some other natural language. A related concept, agentic coding, is broader, covering autonomous task execution by AI agents within a structured workflow that includes goal and task specification, testing, validation, and oversight. In this book, examples in R and Python are shown, and the initial chapters (the ones that focus on statistics) discuss the use of vibe coding, primarily at the conclusion of the chapters. The latter chapters discuss AI in more depth, and go into more detail on its use for coding.
Genre: Non-Fiction > Tech & Devices
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