Learning Science

Artificial intelligence is smarter than humans. It can process information at lightning speed and remain focused on specific tasks without distraction. AI can see into the future, predicting outcomes and even use sensors to see around physical and virtual corners. So why does Intelligence frequently get it so wrong? The answer is us. Humans design the algorithms that define the way that AI works and the processed information reflects an imperfect world.

In July 1995, San Jose Mercury-News reporter Gary Webb found the Big One - the blockbuster story every journalist secretly dreams about - without even looking for it. A simple phone call concerning an unexceptional pending drug trial turned into a massive conspiracy involving the Nicaraguan Contra rebels, L.A. and Bay Area crack cocaine dealers, and the Central Intelligence Agency.

You don't have to be a computer scientist to have discerning conversations about artificial intelligence and technology. We all wonder where we're headed. Even now, technological innovations and machine learning have a daily impact on our lives, and many of us see good reasons to dread the future. Are we doomed to the surveillance society imagined in George Orwell's 1984? Mathematician and philosopher John Lennox believes that there are credible responses to the daunting questions that AI poses.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

Getting into a top-ranked college has never seemed more impossible, with acceptance rates at some elite universities dipping into the single digits. In Who Gets in and Why, journalist and higher education expert Jeffrey Selingo dispels entrenched notions of how to compete and win at the admissions game and reveals that teenagers and parents have much to gain by broadening their notion of what qualifies as a "good college". Hint: It's not all about the sticker on the car window.

Este audiolibro te presentará el mundo digital. La ciencia de datos es uno de los campos más sorprendentes y de tendencia en la era digital. La ciencia de datos es lo que nos hace humanos como somos hoy. No se limita a las tecnologías controladas por computadora, este audiolibro lo guiará para visualizar los hechos digitales y las conexiones de nuestro cerebro con la ciencia de datos, cómo sacar conclusiones de información simple y cómo desarrollar patrones para comprender diferentes soluciones para un problema similar.

Neuroscientists and cognitive scientists have made enormous strides in understanding the brain and how we learn, but little of that insight has filtered down to the way teachers teach. Uncommon Sense Teaching applies this research to the classroom for teachers, parents, and anyone interested in improving education.

From an early age, it is drilled into our heads: Restlessness, distraction, and ignorance are the enemies of success. We’re told that learning is all self-discipline, that we must confine ourselves to designated study areas, turn off the music, and maintain a strict ritual if we want to ace that test, memorize that presentation, or nail that piano recital. But what if almost everything we were told about learning is wrong?

Must Learn KQL - the blog series, the book, the video channel, the merch store After hearing that our customers’ largest barrier to using things like Defender, Microsoft Sentinel, and even reporting for Microsoft Intune is KQL - the query language - that was a wake-up call for me. And, of course, (if you know me) I wanted to do something about it. So, the Must Learn KQL learning was born. KQL is a beautifully simple query language to learn. And believe me – if I can learn it, there’s no question that anyone can learn it. After hearing that from our customers and after researching and ...

Deep Learning with Python (Second Edition) introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you’ll build your understanding through intuitive explanations and clear examples. You’ll quickly pick up the skills you need to start developing deep learning applications.

The culture of “safety” and its intolerance of opposing viewpoints has left many young people anxious and unprepared for adult life. Lukianoff and Haidt offer a comprehensive set of reforms that will strengthen young people and institutions, allowing us all to reap the benefits of diversity, including viewpoint diversity. This is a book for anyone who is confused by what’s happening on college campuses today, or has children, or is concerned about the growing inability of Americans to live and work and cooperate across party lines.

Need networking know-how, but don't know where to turn? Run-don't walk-to the no-nonsense networking guidance offered in this friendly guide! Whether you're a networking administrator or an everyday computer user looking to set up a network in your home or office, Networking for Dummies, seamlessly gets you connected with the basics and gives you the knowledge to work out whatever kinks may come your way-in no time.

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. The book addresses real-life problems faced by practitioners on a daily basis and explains scientifically sound solutions using math, supported by code and examples.

Stylish Academic Writing showcases a range of scholars from the sciences, humanities, and social sciences who write with vividness and panache. Individual chapters take up specific elements of style, such as titles and headings, chapter openings, and structure, and close with examples of transferable techniques that any writer can master.

Leaders already know that the classic approach to strategy - analyze, plan, execute - is losing relevance. But they don't yet know what replaces it. As everyone and everything becomes more interconnected and digitized, how do you operate, compete, and win? Ming Zeng, the former chief of staff and strategy adviser to Alibaba Group's founder, Jack Ma, explains how the latest technological developments, such as artificial intelligence, machine learning, the mobile internet, and cloud computing, are redefining how value is created.

As tech products become more prevalent today, the demand for machine learning professionals continues to grow. But the responsibilities and skill sets required of ML professionals still vary drastically from company to company, making the interview process difficult to predict. In this guide, data science leader Susan Shu Chang shows you how to tackle the ML hiring process. She'll take you through the highly selective recruitment process by sharing hard-won lessons she learned along the way.

Expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues. Discover two comprehensive manuscripts in one audiobook.

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

Millions of people access Microsoft Teams every day to assist with the collaboration it takes to get work done. If you're new to Microsoft Teams, start here. This book will give you must-have insight on chatting, file sharing, organizing teams, using video communication, and more. You'll also see just how you should be doing things, with best-practice recommendations and ideas for integrating Microsoft Teams into your existing workflows.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.