As an author, I run my own business and have a hand in all aspects of my product, from creation to promotion. My work is my passion, so I love to write (and read!) books about women who have that same dedication to their careers. I enjoy seeing these ladies strive for success and how they handle challenges along the way. And, of course, since RomComs are my genre, those challenges often involve a man because where else is a workaholic going to find her soulmate? The witty banter, sizzling sexual tension, snort-laugh moments, and surprising plot twists on the pages of all these books, including mine, are guaranteed to entertain you.
An office rivalry between software developer Emma and app developer Rishi takes an interesting turn when they’re sent to Bangalore to work on a project together.
Back in his home country, Rishi’s family pressures him to get married to a woman of the right caste/religion. Emma offers to create an algorithm to help Rishi find the perfect wife who might be a lot closer than he thinks!
This book does a wonderful job of delving into the challenges of an American woman dating an Indian man as well as the dynamics and relationships within an Indian family. Brooke Burroughs brings India to vibrant life on the page, and I felt as though I was falling in love with the country (and Rishi!) along with Emma.
In Brooke Burroughs's endearing debut novel set in vibrant India, enemies turned allies encounter obstacles in an unexpected multicultural romance only to discover that in the end, love is love.
Emma has always lived her life according to a plan. But after turning down her boyfriend's proposal, everything starts to crumble. In an effort to save the one thing she cares about-her job-she must recruit her colleague, Rishi, to be on her development team...only she may or may not have received the position he was promised. (She did.)
Rishi cannot believe that he got passed over for promotion. To make…
I love pulling back the curtain on how computers work. I want to go from thinking "that's magic" to "that's unbelievably clever but now I understand how it works." Each time I am able to do this feels like a hard-won but therefore meaningful step toward understanding. I want others to experience this empowering shift. I have a PhD in computer science education, and I want to know what helps people learn. More importantly, I want to know how we can use such discoveries to write more effective books. The books I appreciate most are those that demonstrate not only mastery of the subject matter but also mastery of teaching.
Many of my favourite algorithms books give short shrift to designing APIs for the algorithms and data structures that they present. The Sedgewick and Wayne book, by contrast, goes all in on an object-oriented API design. This is my book choice for Java programmers and those interested in larger program design considerations. Clear your calendar: each chapter here is massive, but I think the time investment is worth it. I especially like the chapter that shows how to tune classic algorithms for realizing speedups when working with strings.
This fourth edition of Robert Sedgewick and Kevin Wayne's Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing--including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.
The algorithms in this book represent a body of knowledge developed…
I’ve been fascinated by the news media and technology for as long as I can remember. I successfully campaigned for a VCR as a five-year-old, and watched multiple news programs with my grandfather growing up. Alongside these interests, I managed to read as many books as I possibly could. I’ve managed to somehow parlay that into a job as a researcher, where I study the news media sector and technological transformation. I read everything on this list while I was writing my latest book, and hope you enjoy them as much as I did!
Philip Napoli is a leading media policy expert and was one of the first people to identify some of the problems that emerge when news gets distributed online through social media algorithms.
I love this book because it provides a great narrative of how we got to this point, but also some fantastic suggestions for how policymakers can respond. It’s quite readable for an academic book, and worth checking out.
Facebook, a platform created by undergraduates in a Harvard dorm room, has transformed the ways millions of people consume news, understand the world, and participate in the political process. Despite taking on many of journalism's traditional roles, Facebook and other platforms, such as Twitter and Google, have presented themselves as tech companies-and therefore not subject to the same regulations and ethical codes as conventional media organizations. Challenging such superficial distinctions, Philip M. Napoli offers a timely and persuasive case for understanding and governing social media as news media, with a fundamental obligation to serve the public interest.
It’s been fantastic to work in computer vision, especially when it is used to build biometric systems. I and my 80 odd PhD students have pioneered systems that recognise people by the way they walk, by their ears, and many other new things too. To build the systems, we needed computer vision techniques and architectures, both of which work with complex real-world imagery. That’s what computer vision gives you: a capability to ‘see’ using a computer. I think we can still go a lot further: to give blind people sight, to enable better invasive surgery, to autonomise more of our industrial society, and to give us capabilities we never knew we’d have.
Richard’s authoritative leading textbook excellently describes the whole field of computer vision. It starts with the sensor, moves to image formation followed by feature extraction and grouping, and then by vision analysis. It’s pragmatic too, with excellent descriptions of applications. And there is a ton of support material. This is a mega textbook describing the whole field of computer vision.
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.
More than just a source of "recipes," this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are…
I am a book publicist and President of Westwind Book Marketing, a public relations and marketing firm that has a special knack for working with authors to help them get all the publicity they deserve and more. I work with bestselling authors and self-published authors promoting all types of books, whether it's their first book or their 15th book. I’ve handled publicity for books by CEOs, CIA Officers, Navy SEALS, Homemakers, Fitness Gurus, Doctors, Lawyers, and Adventurers. My clients have been featured by Good Morning America, FOX & Friends, CNN, ABC News, New York Times, Nightline, TIME, PBS, LA Times, USA Today, Washington Post, Woman's World, and Howard Stern.
In Book Funnels & Amazon Ads, Alex draws
from his experience of working with hundreds of authors. He delves into Amazon
Advertising and reveals how to leverage this unique opportunity to your
advantage. Amazon ads can be very effective for authors but you need to educate
yourself before diving in. There is too much to know to just ‘wing it.’ This
book was written by a person who is first a techie guy and understands Amazon
algorithms like you and I will never comprehend.
Alex Strathdee can help. He’s built a successful Amazon Ads consulting business with over $300,000 in ad budget and this book shows you how he did it. If you need to scale your marketing, then you must learn these techniques.
Do you understand book funnels?
He will walk you through every step to build profitable book funnels. You’ll learn the importance of social proof and how to pick a winning title.
I've had a long-time interest in two things: mathematics and social issues. This is why I got degrees in social work (Masters) and sociology (PhD) and eventually focused on the quantitative aspects of these two areas. Social Workers Count gave me the chance to marry these two interests by showing the role mathematics can play in illuminating a number of pressing social issues.
As I write these lines, artificial intelligence (AI) is getting a lot of attention.
This is largely due to ChatGpt recently bursting onto the scene. But even before ChatGpt began making its mark, AI was often in the news. Some have expressed worry that it will take our jobs, others that it will reinforce systemic oppression by making racially or otherwise discriminatory decisions, and some have even voiced concerns that one day a superintelligent AI might pose an existential threat to humanity.
In the midst of all this, what might get lost is what AI is, what it's capable of doing, and what its limitations are. Wenger's book is intended to address all of these questions. It manages to do so in a way which goes into some of the mathematics of AI systems and yet remain accessible to a lay audience.
Artificial intelligence is everywhere―it’s in our houses and phones and cars. AI makes decisions about what we should buy, watch, and read, and it won’t be long before AI’s in our hospitals, combing through our records. Maybe soon it will even be deciding who’s innocent, and who goes to jail . . . But most of us don’t understand how AI works. We hardly know what it is. In "Is the Algorithm Plotting Against Us?", AI expert Kenneth Wenger deftly explains the complexity at AI’s heart, demonstrating its potential and exposing its shortfalls. Wenger empowers readers to answer the question―What…
I am a Reader in the Mathematics Education Centre at Loughborough University in the UK. I have always loved mathematics and, when I became a PhD student and started teaching, I realized that how people think about mathematics is fascinating too. I am particularly interested in demystifying the transition to proof-based undergraduate mathematics. I believe that much of effective learning is not about inherent genius but about understanding how theoretical mathematics works and what research tells us about good study strategies. That is what these books, collectively, are about.
This book provides a systematic account of how to understand and structure mathematical proofs. Its approach is almost entirely syntactic, which is the opposite of how I naturally think – I tend to generate arguments based on examples, diagrams, and conceptual understanding. But that difference, for me, is precisely what makes this book so valuable. Solow gives a no-nonsense, practical, almost algorithmic approach to interpreting logical language and to tackling the associated reasoning. His book thereby provides the best answer I know of to the “How do I start?” problem so often encountered when students begin constructing proofs.
This text makes a great supplement and provides a systematic approach for teaching undergraduate and graduate students how to read, understand, think about, and do proofs. The approach is to categorize, identify, and explain (at the student's level) the various techniques that are used repeatedly in all proofs, regardless of the subject in which the proofs arise. How to Read and Do Proofs also explains when each technique is likely to be used, based on certain key words that appear in the problem under consideration. Doing so enables students to choose a technique consciously, based on the form of the…
I build and use emerging technological innovations in business, and I also teach others how they might too! I’m a serial entrepreneur and a Professor at the Wharton School of the University of Pennsylvania. As an entrepreneur, I co-founded and developed the core IP for Yodle Inc, a venture-backed firm that was acquired by Web.com. I’m now the founder of Jumpcut Media – a startup using data and Web3 technologies to democratize opportunities in Film and TV. In all this work, I'm often trying to assess how emerging technologies may affect business and society in the long run and how I can apply them to create new products and services.
This book provides an excellent description of the various kinds of machine learning approaches and asks the question of whether there will be a Master Algorithm, one single (universal) algorithm that learns all kinds of tasks from data. The author, Pedro Domingos, introduces the different approaches to building intelligence and the research tribes exploring them – Symbolists (with its foundations in Philosophy and Logic), Connectionists (foundations in Neuro/Cognitive Science), Evolutionaries (foundations in Evolutionary Biology), Bayesians (statistical foundations), and Analogizers (Psychology). He also introduces some of his own ideas on what the master machine learning algorithm might look like. It’s a really useful primer for those who are not deeply immersed in machine learning but it’s written for readers with at least a basic engineering and computer science background.
Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. And in the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.Machine learning is the automation of discovery,the scientific method on steroids,that enables intelligent robots and…
I am Professor of Computer Science at Stony Brook University, and have spent the past thirty years thinking/teaching/writing about algorithms. Algorithms are the really cool thing about computer science, for they form the ideas behind any interesting computer program. And algorithms turn out to be the ideas behind many interesting aspects of life that have nothing to do with computers. I have written six books on algorithms, programming, gambling, and history –including the ranking of the historical significance of all the people in Wikipedia.
Knuth’s unique mix of playfulness and rigor came to define computer science as an intellectual discipline: computer science didn’t really have anything to do with computers, but everything to do with a particular way of seeing the world. Just browse and wonder at the beauty and precision achieved in these books.
Volume 3 (Sorting and Searching) is my personal favorite, and I encourage you to start there. During the pandemic, I finally got around to reading Volume 4A (Combinatorial Algorithms), which was published thirty plus years after Volume 3. It was the same feeling I had watching the movie The Phantom Menace years after growing up with the original Star Wars trilogy. I had forgotten just how unique and distinctive Knuth’s Art of Computer Programming is.
The bible of all fundamental algorithms and the work that taught many of today's software developers most of what they know about computer programming.
-Byte, September 1995
I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up.
-Charles Long
If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole…
I’m a mathematics professor who ended up writing the internationally bestselling novel The Death of Vishnu (along with two follow-ups) and became better known as an author. For the past decade and a half, I’ve been using my storytelling skills to make mathematics more accessible (and enjoyable!) to a broad audience. Being a novelist has helped me look at mathematics in a new light, and realize the subject is not so much about the calculations feared by so many, but rather, about ideas. We can all enjoy such ideas, and thereby learn to understand, appreciate, and even love math.
A primary reason to love math is because of its usefulness. This book shows two sides of math’s applicability, since it is so ubiquitously used in various algorithms.
On the one hand, such usage can be good, because statistical inferences can make our life easier and enrich it. On the other, when these are not properly designed or monitored, it can lead to catastrophic consequences. Mathematics is a powerful force, as powerful as wind or fire, and needs to be harnessed just as carefully.
Cathy O’Neil’s message in this book spoke deeply to me, reminding me that I need to be always vigilant about the subject I love not being deployed carelessly.
'A manual for the 21st-century citizen... accessible, refreshingly critical, relevant and urgent' - Financial Times
'Fascinating and deeply disturbing' - Yuval Noah Harari, Guardian Books of the Year
In this New York Times bestseller, Cathy O'Neil, one of the first champions of algorithmic accountability, sounds an alarm on the mathematical models that pervade modern life -- and threaten to rip apart our social fabric.
We live in the age of the algorithm. Increasingly, the decisions that affect our lives - where we go to school, whether we get a loan, how much we pay for insurance - are being made…
