Bin Yu and Rebecca Barter employ the innovative Predictability, Computability, and Stability (PCS) framework to assess the trustworthiness and relevance of data-driven results relative to three sources of uncertainty that arise throughout the data science life cycle: the human decisions and judgment calls made during data collection, cleaning, and modeling. By providing real-world data case studies, intuitive explanations of common statistical and machine learning techniques, and supplementary R and Python code, Veridical Data Science offers a clear and actionable guide for conducting responsible data science.

Uploaded March 2025

While Commodore 64 sold at least twice as many units as other home computers of its time, like the Apple II, ZX Spectrum, or Commodore Amiga, it is strangely forgotten in many computer histories. In Too Much Fun, Jesper Juul argues that the C64 was so popular because it was so versatile, a machine developers and users would reinvent again and again over the course of 40 years.

Uploaded March 2025

Make: The Complete Guide to Tinkercad embraces the concept of "learn by doing," using 17 fun projects to transform the reader from a novice into a creator of video assets and objects ready for 3D printing. This comprehensive manual teaches the intricacies of the Tinkercad interface, how to model sophisticated objects, and use AI as a tool to solve design challenges.

The vital story of how women designers and researchers pioneered the field of interaction and user experience design for software and digital interfaces. Framed against the backdrop of contemporary waves of feminism and the history of computing design, In through the Side Door foregrounds the stories of the women working in the field of computing and the emergent discipline of interaction design as the graphical user interface was developed.

Uploaded March 2025

Can an algorithm be democratic? And how can we understand algorithms not only as technical, but also as social and political phenomena? Democratic Algorithms offers theoretically and empirically informed perspectives on how we can imagine and design algorithms for a democratic society, and what we even mean by that.

Uploaded March 2025

This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare.

Uploaded March 2025

By applying universal rules of software architecture, you can dramatically improve developer productivity throughout the life of any software system. Now, building upon the success of his best-selling books Clean Code and The Clean Coder, legendary software craftsman Robert C. Martin (“Uncle Bob”) reveals those rules and helps you apply them.

Uploaded March 2025

In ChatGPT and the Future of AI, the sequel to The Deep Learning Revolution, Terrence Sejnowski offers a nuanced exploration of large language models (LLMs) like ChatGPT and what their future holds. Sejnowski begins by describing the debates surrounding LLMs’ comprehension of language and exploring the notions of “thinking” and “intelligence.” He then takes a deep dive into the historical evolution of language models, focusing on the role of transformers, the correlation between computing power and model size, and the intricate mathematics shaping LLMs.

Uploaded March 2025

An engaging and comprehensive exploration of how fundamental ideas in political and legal thought shape the governance of blockchain communities, and are, in turn, shaped by blockchain technology. In Blockchain Governance, Primavera De Filippi, Wessel Reijers, and Morshed Mannan give an accessible, critical overview of legal and political issues related to blockchain technology, now the foundation of a multi-billion-dollar industry.

Uploaded March 2025~

In Beautiful Math, Chris Bernhardt explores the mathematics at the very heart of the information age. He asks questions such as: What is information? What advantages does digital information have over analog? How do we convert analog signals into digital ones? What is an algorithm? What is a universal computer? And how can a machine learn?The four major themes of Beautiful Math are information, communication, computation, and learning.

Uploaded March 2025