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100% OFF Udemy Coupon - (Verified) For Aug 2021 - Python For Data Science


When compared to all other programming language, python is extremely simple, easy to learn, interpret and implement. Due to this reason it became very popular and trending programming right now. The job demand for python programmers are high. Python engineers have some of the highest salaries in the industry. There are plenty of Python scientific packages for data visualization, machine learning, natural language processing, complex data analysis and more.

PySpark for Data Science - Advanced ($89.99 to FREE)


This module in the PySpark tutorials section will help you learn about certain advanced concepts of PySpark. In the first section of these advanced tutorials, we will be performing a Recency Frequency Monetary segmentation (RFM). RFM analysis is typically used to identify outstanding customer groups further we shall also look at K-means clustering. Next up in these PySpark tutorials is learning Text Mining and using Monte Carlo Simulation from scratch. Pyspark is a big data solution that is applicable for real-time streaming using Python programming language and provides a better and efficient way to do all kinds of calculations and computations.

100% Free Udemy Certificate Courses - Learn Machine learning & AI (Including Hands-on 3 Projects)


Do you feel overwhelmed going through all the AI and Machine learning study materials? These Machine learning and AI projects will get you started with the implementation of a few very interesting projects from scratch. The first one, a Web application for Object Identification will teach you to deploy a simple machine learning application. The second one, Dog Breed Prediction will help you building & optimizing a model for dog breed prediction among 120 breeds of dogs. This is built using Deep Learning libraries.

Making the most of your day: online learning for optimal allocation of time Machine Learning

We study online learning for optimal allocation when the resource to be allocated is time. Examples of possible applications include a driver filling a day with rides, a landlord renting an estate, etc. Following our initial motivation, a driver receives ride proposals sequentially according to a Poisson process and can either accept or reject a proposed ride. If she accepts the proposal, she is busy for the duration of the ride and obtains a reward that depends on the ride duration. If she rejects it, she remains on hold until a new ride proposal arrives. We study the regret incurred by the driver first when she knows her reward function but does not know the distribution of the ride duration, and then when she does not know her reward function, either. Faster rates are finally obtained by adding structural assumptions on the distribution of rides or on the reward function. This natural setting bears similarities with contextual (one-armed) bandits, but with the crucial difference that the normalized reward associated to a context depends on the whole distribution of contexts.

Personalized Education in the AI Era: What to Expect Next? Artificial Intelligence

The objective of personalized learning is to design an effective knowledge acquisition track that matches the learner's strengths and bypasses her weaknesses to ultimately meet her desired goal. This concept emerged several years ago and is being adopted by a rapidly-growing number of educational institutions around the globe. In recent years, the boost of artificial intelligence (AI) and machine learning (ML), together with the advances in big data analysis, has unfolded novel perspectives to enhance personalized education in numerous dimensions. By taking advantage of AI/ML methods, the educational platform precisely acquires the student's characteristics. This is done, in part, by observing the past experiences as well as analyzing the available big data through exploring the learners' features and similarities. It can, for example, recommend the most appropriate content among numerous accessible ones, advise a well-designed long-term curriculum, connect appropriate learners by suggestion, accurate performance evaluation, and the like. Still, several aspects of AI-based personalized education remain unexplored. These include, among others, compensating for the adverse effects of the absence of peers, creating and maintaining motivations for learning, increasing diversity, removing the biases induced by the data and algorithms, and the like. In this paper, while providing a brief review of state-of-the-art research, we investigate the challenges of AI/ML-based personalized education and discuss potential solutions.

Policy Optimization as Online Learning with Mediator Feedback Machine Learning

Policy Optimization (PO) is a widely used approach to address continuous control tasks. In this paper, we introduce the notion of mediator feedback that frames PO as an online learning problem over the policy space. The additional available information, compared to the standard bandit feedback, allows reusing samples generated by one policy to estimate the performance of other policies. Based on this observation, we propose an algorithm, RANDomized-exploration policy Optimization via Multiple Importance Sampling with Truncation (RANDOMIST), for regret minimization in PO, that employs a randomized exploration strategy, differently from the existing optimistic approaches. When the policy space is finite, we show that under certain circumstances, it is possible to achieve constant regret, while always enjoying logarithmic regret. We also derive problem-dependent regret lower bounds. Then, we extend RANDOMIST to compact policy spaces. Finally, we provide numerical simulations on finite and compact policy spaces, in comparison with PO and bandit baselines.

Data Analytics: SQL for newbs, beginners and marketers


Online Courses Udemy - Data Analytics: SQL for newbs, beginners and marketers, Dominate data analytics, data science, and big data Created by Lazy Programmer Inc English [Auto-generated] Students also bought Data analyzing and machine learning Hands-on with KNIME Machine Learning Practical: 6 Real-World Applications Careers in Data Science A-Z Statistics Masterclass for Data Science and Data Analytics Text Mining and Natural Language Processing in R Preview this course GET COUPON CODE Description It is becoming ever more important that companies make data-driven decisions. With big data and data science on the rise, we have more data than we know what to do with. One of the basic languages of data analytics is SQL, which is used for many popular databases including MySQL, Postgres, SQLite, Microsoft SQL Server, Oracle, and even big data solutions like Hive and Cassandra. I'm going to let you in on a little secret. Most high-level marketers and product managers at big tech companies know how to manipulate data to gain important insights.

Real-Time Optimisation for Online Learning in Auctions Machine Learning

In display advertising, a small group of sellers and bidders face each other in up to 10 12 auctions a day. In this context, revenue maximisation via monopoly price learning is a high-value problem for sellers. By nature, these auctions are online and produce a very high frequency stream of data. This results in a computational strain that requires algorithms be real-time. Unfortunately, existing methods inherited from the batch setting suffer O($\sqrt t$) time/memory complexity at each update, prohibiting their use. In this paper, we provide the first algorithm for online learning of monopoly prices in online auctions whose update is constant in time and memory.

Understand big data in Excel with this discounted online course


TL;DR: The 2020 Master Microsoft Excel & Power BI Certification Bundle is on sale for £27.19 as of Oct. 2, saving you 97% on list price. "Data science" seems to be all the rage these days. The buzzword sounds super fancy, but when you actually break it down, it's just the ability to wrangle big data, break it down, and use it to make decisions. From self-driving cars in the automotive industries, to risk management in insurance, to recommending what Netflix series to binge-watch next, data science is behind it all. And you can use a tool that's been around since the '80s to familiarise yourself with the data-driven world: good ol' Microsoft Excel.

A reading list for uncertain times


From an incisive ethnography of predictive policing to a compelling indictment of technology-enabled learning tools, the books on this year's fall reading list offer valuable context to the myriad challenges currently facing humanity. Dive deep into a public health disaster shrouded in secrecy, sit with the uncomfortable questions raised by a fictional foray into the future of intimacy, confront the challenges to sustainable development posed by environmental racism, and learn what a QR-coded chicken in rural China portends about the future of agriculture. When you are through, sit back and marvel at the odds stacked against humanity from the start with an entertaining romp through evolution and then leave your earthly worries behind with an ambitious tour of the Solar System. —Valerie Thompson Reviewed by Ivor Knight 1 Through a series of chance events, the pathogen we now know as severe acute respiratory syndrome coronavirus 2 emerged in 2019 and infected millions of humans within a span of 6 months. But chance has driven more than just the planet's latest pandemic. In his new book, A Series of Fortunate Events: Chance and the Making of the Planet, Life, and You , Sean B. Carroll takes readers on an entertaining tour of biological discovery that emphasizes the dominant role played by chance in shaping the conditions for life on Earth. Along the way, he provides insights and humor that make the book a quick, lively read that both educates and entertains. Carroll begins with one of the most consequential chance events to have occurred in the history of our planet: the Cretaceous-Paleogene asteroid impact on the Yucatán Peninsula that resulted in the extinction of the dinosaurs and expansion of mammals. Given Earth's rotational speed, if the asteroid had hit 30 minutes earlier or later, scientists believe it would have made a much less consequential impact, landing in either the Atlantic or Pacific Ocean. If that had happened, there might still be dinosaurs today, but no humans. As he does throughout the book, Carroll compares the example from science with an example from popular culture, describing the comedian Seth MacFarlane's good fortune to have narrowly missed (by 30 minutes) one of the flights that was hijacked on 11 September 2001. Fundamental topics such as the roles that mutation and natural selection play in the evolution of diverse life-forms, the genetics of human reproduction, cellular mechanisms of acquired immunity, and the development of cancer are all treated within a framework where chance dominates. Carroll explains in detail how chance creates the genetic diversity upon which natural selection acts and results in the richness of species on Earth, as well as how random combinations among just 163 gene segments make possible a human immune system that can produce up to 10 billion different antibodies. Readers will likely be particularly interested to learn that their genome is only one of the 70 trillion possibilities that could have been produced by their parents. Written in a conversational style, the book reads like an updated version of Jacques Monod's 1970 Chance and Necessity that speaks directly to the reader, making complex subject matter more accessible. There is also a suggested reading list and an extensive bibliography included for further exploration. Carroll's central argument, that we are all here by luck, is certainly clear and compelling. What we choose to do with that luck, however, is where things really get interesting. Books such as this remind us to make our unlikely time here count. Reviewed by Gillian Bowser 2 Does a hurricane discriminate between the wealthy and the poor? Do earthquakes target specific victims? How does systemic racism influence development goals? In academic explorations of sustainable development and environmental responsibilities, our assumptions about the relationship between income and energy consumption remain largely rooted in the idea that social inequalities decrease as countries develop, thus reducing environmental inequality. No such relationship appears to actually exist. In his sobering but essential new book, Unsustainable Inequalities , economist Lucas Chancel explores the intersections of social justice and environmental sustainability with a focus on global goals established at the 2012 United Nations Conference on Sustainable Development, which informed the underlying philosophy of the 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC) ([ 1 ][1]). Framing his narrative through the lens of intragenerational economic inequalities, he identifies social inequality as a core driver of environmental unsustainability that leads to a vicious circle wherein the rich consume more and the poor lose access to environmental resources and become increasingly vulnerable to environmental shocks. In 1987, the World Commission on Environment and Development issued a report called “Our Common Future” that defined sustainable development as “development that meets the need of the present without compromising the ability of future generations to meet their own needs” ([ 2 ][2]). The idea of intergenerational environmental equity became a cornerstone concept, shifting climate policy toward the common but differentiated responsibilities enshrined in the UNFCCC. Yet questions about intergenerational responsibility and the equitable impacts of climate change and environmental degradation remain. Environmental racism, wherein communities of color are disproportionately exposed to environmental risks, is inseparable from social justice, Chancel argues, and the attainment of sustainable development that also protects the environment across generations is “extremely difficult” without first addressing economic inequality within a single generation. The notion that we may be able to attain sustainable development and achieve equal responsibility for environmental degradation feels more unreachable than ever in a world upended by a global pandemic. In prepandemic times, many nations had already failed to implement or participate in local and global environmental justice efforts, and taxation schemes to level responsibilities for environmental pollution have proven wildly unpopular. And while Chancel argues that common indicator frameworks such as the United Nations' Sustainable Development Goals encourage nations to learn from one another, the continued rise of social inequality is a stark reminder of the difficult road ahead. Reviewed by Kanwal Singh 3 As the pandemic forces so many school systems and learning institutions to move online, the desire to educate students well using online tools and platforms is more pressing than ever. But as Justin Reich illustrates in his new book, Failure to Disrupt , there are no easy solutions or one-size-fits-all tools that can aid in this transition, and many recent technologies that were expected to radically change schooling have instead been used in ways that perpetuate existing systems and their attendant inequalities. The first half of the book discusses the brief histories, limited successes, and challenges of three types of large-scale technology-driven learning environments: instructor-guided, such as lectures taught through massive open online courses (MOOCs); algorithm-guided (e.g., Khan Academy); and peer-guided (e.g., the online coding community known as Scratch). Reich gives a solid accounting of the conditions needed for success with these models, the difficulties and limitations involved in adopting them in K–12 schooling, and the challenges that arise when we attempt to compare different approaches to one another. He argues that although we might think that the availability of a technology is its biggest limiter, the truth is that educational systems are simply not constructed to allow for experimentation and new ways of learning. Reich describes himself as committed to “methodological pluralism.” He supports the use of an array of learning tools and mechanisms, although he confesses to a particular admiration for peer-guided environments. He argues, however, that the incentive structures in formal education do not encourage the more innovative and deeper learning that can blossom in these environments. If we insist on maintaining current methods of assessment and ranking, which center on individual achievement, then peer-guided instruction will remain relegated to the sidelines. The second part of the book expands on the challenges of implementing educational technologies. Reich's main argument here is that educational systems are inherently conservative and that change will happen, albeit slowly and incrementally, only if technology designers, teachers, and administrators work in partnership to understand the desired learning goals and the parameters that define and constrain the learning environments. One of the most intractable pieces of the educational technology puzzle is the need to effectively conduct large-scale assessment, especially when the skills being assessed are not things that computers can do. Here, Reich cites a humorous example of an automated grading system giving high marks to an essay that begins with the technically grammatically correct sentence: “Educatee on an assassination will always be a part of mankind.” At the end of the book, Reich offers four questions that he finds especially useful to consider when examining a new large-scale educational technology. Perhaps the most useful question is the first: “What's new?” Despite what “edtech evangelists” might claim, new technologies often have closely related ancestors that can help predict their success, he argues. In the end, however, new technologies alone are unlikely to have a substantial impact on schooling. We must also be open to changing educational goals and expectations according to the possibilities offered by emergent technologies. Reviewed by Arti Garg 4 In Blockchain Chicken Farm , Xiaowei Wang reveals the myriad ways that technology is transforming our lives. They unveil, for example, the unexpected connections that exist between industrial oyster farming in rural China, livestream-fueled multilevel marketing schemes in the United States, and the app-enabled gig economy in which Chinese influencers participate. Following the threads of places and people woven together by new technologies, Wang helps readers trace the patterns emerging in the tapestry of our tech-infused world. Each chapter provides a view into not just how we use technology but why and to what end. Emphasizing the often-hidden human engine that powers our app-driven economy, Wang exposes the flaw in our tendency to conflate societal and cultural aspirations with the promises of technology and challenges us to honestly measure what value technology delivers. In the 21st century, they argue, we demand that technologists solve the problems that our governments and communities have not. In doing so, we inadvertently empower companies to exploit and amplify those same problems. Most of Wang's vignettes relate to Chinese agriculture. This decision, which roots the narrative in the visceral language of human sustenance, grounds the heady subject matter. The titular example takes readers to the GoGoChicken farm in Sanqiao, a “dreamlike” village that sits in one of the poorest regions in China. Here, Wang introduces the straw-hatted “Farmer Jiang,” who has partnered with his village government and a blockchain company to sell free-range chickens via an e-commerce site. Jiang's chickens sell for RMB 300 (∼$35) each, an amount equal to 6% of the average annual household income in that part of China. Wang explains that high-profile failures of regulatory oversight have left many Chinese with a deep distrust of the food supply chain and that upper-class Chinese urbanites will pay a premium for reassurance about food safety, which, in this case, takes the form of a vacuum-sealed chicken that comes with a QR code revealing blockchain-logged details of its life on the farm. Wang suggests that Americans, driven by concerns over animal welfare, may desire similar reassurance about their food's provenance. In both China and America, they observe, technology allows the upper class to buy its way around governmental and societal shortcomings at prices that are out of reach for most people. Technology does not correct the intrinsic problems, and most cannot reap the benefits of the technological “solutions.” Without resorting to an overly romanticized notion of rural wisdom, Wang treats individuals like Jiang, whose future remains uncertain owing to the vagaries of e-commerce supply chains, with respect and empathy. Because of this, they largely succeed in their goal of reframing our understanding of technology as neither the cause of nor the solution to our problems but rather as a force reshaping the human experience in fundamental ways. Reviewed by Heather Bloemhard 5 The Secret Lives of Planets by Paul Murdin includes a plethora of information about our Solar System. Murdin covers planets, asteroids, moons, dwarf planets, and more, approximately one per chapter. Even exoplanets—the planets that orbit a star other than our Sun—are referenced frequently, although not in their own chapter. Using only a few images, Murdin illustrates the historical and physical concepts that surround each of these elements in prose peppered with anecdotes from his own career as an astronomer. While the book's tone is pleasant and conversational, the discussions are often technical in nature, and I worry that some readers may be frustrated by its many tangents and loose organizational structure. For example, in his discussion of the formation of Mercury, Murdin references the formation of exoplanets, the discovery of 'Oumuamua, and Earth's fossil record. The same chapter also refers to Earth and Venus to help explain orbital eccentricity and precession, but this analogy may fall short for lay readers. I was also disappointed that Murdin relied almost exclusively on the accomplishments of European men to tell the story of how our understanding of the Solar System emerged over time. He writes, for example, of Nicolaus Copernicus's revelations about the geometry of our solar system but neglects the work of Muslim astronomers who developed models of heliocentric orbits hundreds of years earlier. Murdin is far from alone in this misstep, but it is well worth striving to do better. Despite these criticisms, every reader will learn something from this ambitious book. Did you know, for example, that some scientists once believed there were oases of vegetation on Mars, or that others believed that martians might try to colonize Earth? From the exchange of planetary material by way of meteorites to the formation of asteroids, Murdin covers a wide range of astronomical topics, including the aurora of Jupiter, the mysteries of Uranus, and the potential of the moons of Jupiter and Saturn to support recognizable life. I found Murdin's personal recollections to be the most compelling feature of The Secret Lives of Planets . He tells the story of how, as a student, he observed the shadows cast by the tops of clouds of different heights on Venus using a telescope similar to the one used by Galileo and uses this anecdote as a starting point to explain what the Italian astronomer discovered about the planet. Recounting the time he observed the launch of Cassini-Huygens, a probe sent to Saturn's moon Titan, Murdin explains what scientists had hoped to learn from this mission and what they ended up discovering. He also discusses attending the 2006 International Astronomical Union conference, where a debate was held about the definition of a planet, and reveals what it was like to cast a vote on the final decision. In the end, there is much to recommend The Secret Lives of Planets as an introductory text on our solar system. Reviewed by Peter Reczek 6 Modern cancer therapies are often the result of years of targeted research and development, making it easy to forget that many of the field's early breakthroughs had as much to do with chance as they did with preparation. In The Great Secret , Jennet Conant recounts one such breakthrough, which was made in the wake of a deadly disaster. Conant's engrossing story is set in the Italian port town of Bari, which was used as an important staging area for the distribution of supplies supporting Allied troops as they pushed north through Italy during World War II. On 2 December 1943, a day that would later be referred to as “a little Pearl Harbor,” German military aircraft sank more than 20 Allied ships anchored in Bari, leading to the loss of more than 1000 Allied servicemen and Italian civilians. Lieutenant Colonel Stewart Alexander, a medical officer attached to General Eisenhower's headquarters in North Africa, was sent to coordinate medical relief efforts. In Bari, Alexander found “a nightmarish scene.” In the aftermath of the air raid, “The walking wounded staggered in [to the hospital] unaided, suffering from shock, burns, and exposure after having been in the cold water for hours before being rescued. Others had to be supported, as they cradled fractured arms in improvised slings or dragged mangled limbs…Almost all of them were covered in thick, black crude oil,” writes Conant. In addition to the acutely injured, Alexander discovered victims whose injuries had emerged days after the attack and could not be attributed to the percussive effects of the bombing. After analyzing the positions of the ailing seamen, Alexander reported that an American Liberty ship, the John Harvey , was the source of the problem, speculating that it likely contained a secret cache of nitrogen mustard (i.e., mustard gas). Both the American and British governments denied any such cache, but Conant reveals that Alexander persisted, and his controversial report—which, crucially, documented a decrease in white blood cell counts in the victims—was accepted by the Allied High Command with a classification of “Secret.” After the war, Colonel C. P. “Dusty” Rhoads, who had been Alexander's superior during the Bari investigation, reasoned that an agent that reduced white blood cells might be useful in treating some forms of leukemia. While serving as the first director of the Sloan Kettering Institute, Rhoads oversaw a clinical trial to test nitrogen mustards as potential therapeutic agents for the treatment of neoplastic disease. The results exceeded expectations. “In their first attempt to treat patients with inoperable lung cancer with nitrogen mustard, the Memorial team reported that of the thirty-five patients, 74 percent showed some clinical improvement” writes Conant. Many similar compounds, collectively known as alkylating agents, are still the foundation of the combination chemotherapy used to treat some forms of leukemia. Drawing largely from archival research, Conant relies on a loose conversational style to convey a fast-paced medical detective story that demonstrates how careful scientific observation can yield unexpected benefits and serves as a reminder of the difficult choices made by governments to balance public health and secrecy in matters of security. Reviewed by Esha Mathew 7 In quantum physics, entanglement is a property wherein two particles are inextricably linked. Put another way, entangled particles are never truly independent of each other, no matter the distance between them. It is fitting then that Entanglements is an anthology of short stories about inextricably linked people and the impact of emerging technologies on their relationships. A talented set of authors, with deft editing by Sheila Williams, explore the full spectrum of intimacy and technology to great effect. As an added visual treat, illustrations by Tatiana Plakhova punctuate each story with a blend of science, mathematics, and art that complements the subject matter. Even with the length limitations of a short story, the world-building in this compilation is frequently full and often insidiously terrifying, particularly in those stories that use the familiar as breadcrumbs to lure the reader in. The very first tale, “Invisible People” by Nancy Kress, begins with a mundane morning routine and carefully layers in a story about two parents reeling from an unsanctioned genetic experiment on their child. In “Don't Mind Me,” Suzanne Palmer uses the shuffle between high school classes as a foundation on which to build a story about how one generation uses technology to enshrine its biases and inflict them on the next. The ethical implications in these stories offer fodder enough for plenty of late-night discussions. It is also chilling how entirely possible many of the fictional futures seem. But looking forward need not always be bleak. This volume balances darker-themed stories with those in which technology and people collide in uplifting and charming ways. In Mary Robinette Kowal's “A Little Wisdom,” for example, a museum curator, aided by her robotic therapy dog–cum–medical provider, finds the courage within herself to inspire courage in others and save the day. Meanwhile, in Cadwell Turnbull's “Mediation,” a scientist reeling from a terrible loss finally accepts her personal AI's assistance to start the healing process. And in arguably the cheekiest tale in this compilation, “The Monogamy Hormone,” Annalee Newitz tells of a woman who ingests synthetic vole hormones to choose between two lovers, delivering a classic tale of relationship woes with a bioengineered twist. With such a dizzying array of technologies discussed in relation to a range of human emotion and behavior, readers may experience cognitive whiplash as they move from one story to the next. But it is definitely worth the risk. The 10 very different thought experiments presented in this volume make for a fun ride, revealing that human relationships will continue to be as complicated and affirming in the future as they are today. I would recommend the Netflix approach to this highly readable collection: Binge it in one go, preferably with a friend. Reviewed by Joseph B. Keller 8 The U.S. police system is experiencing a reckoning. Protesters across the country (and around the world) have taken to the streets, arguing that police brutality disproportionately harms minority communities, and the current value of policing is being debated by city councils, lawmakers, and members of the news media. Into this tumultuous context enters Sarah Brayne's book, Predict & Surveil: Data, Discretion, and the Future of Policing . A sociologist by training, Brayne synthesizes interview data and field notes from 5 years of observation within the Los Angeles Police Department, employing a firsthand ethnographic approach to reveal how big data are currently used in tech-forward police departments in America. She chronicles both consequential and mundane interactions between officers, civilians, and data. For example, she documents officers uploading license plate numbers, field interview notes, traffic citations, and potential gang affiliations onto a private industry data platform, as well as their active surveillance of hotspots in Los Angeles predicted to be criminogenic. This fly-on-the-wall perspective captures the human aspect of a police force grappling with automated systems and machine-learning decisions in real time, juxtaposing the experiences of individual officers with institutional directives being handed down from administrators and lawmakers. Many police departments contend that the adoption of predictive analytics can improve objectivity and transparency, reduce bias, and increase accountability. Yet Brayne's book reveals how few of these metrics actually improve with predictive policing and exposes the scant evidence that supports the idea that it reduces crime rates. On the contrary, she insists, predictive policing raises glaring civil rights concerns and reinforces harmful racial biases. We all leave digital traces throughout our daily lives, and innocent people can be caught in the dragnet and cataloged in a digital criminal justice system, where a case can be built from benign data. Police unions, Brayne notes, often vehemently oppose the tracking of their own officers. She records incidents of officers turning off their car locator signals, for example, as well as other tactics used to thwart tech-infused managerial oversight. Many officers view policing as an art form rather than a scientific system that can be optimized. To some, big data policing threatens their sense of police instincts and identity. “They worry that they will become nothing more than line workers and insist that their years of accumulated experiential knowledge is irreplaceable,” observes Brayne. Brayne's book raises timely issues relevant to mass surveillance and policing amid a growing debate about facial recognition systems, which makes their omission from this work notable. Although banned in several major American cities, these systems remain a common tool for identifying potential offenders, despite abundant evidence of dangerous inconsistencies. Predictive policing can drive societal inequalities, but Brayne suggests that reducing instances of general police contact may mitigate disparities. In addition to offering immediate recommendations for changing law enforcement in the digital age, she asserts that effective programmatic reforms are typically influenced by external social organizing and guided by communities. (The likelihood of real transformation from within the police system is small, she believes.) For judicial and policing institutions genuinely seeking reform, this book provides powerful observations and analysis that suggest how we can begin. 1. [↵][3]Paris Agreement to the United Nations Framework Convention on Climate Change, 12 December 2015, TIAS No. 16-1104. 2. [↵][4]World Commission on Environment and Development, Our Common Future (Oxford Univ. Press, 1987). [1]: #ref-1 [2]: #ref-2 [3]: #xref-ref-1-1 "View reference 1 in text" [4]: #xref-ref-2-1 "View reference 2 in text"