Art Of The Race V17

- Encapsulating the speed, noise, excitement and color of Formula 1, and highlighting the key moments of each race as the 2017 season unfolded - Art of The Race, V17 is book 4 in a series of collaborations with Art of Publishing Limited - Darren Heath is one of the pre-eminent photographers in F1 today, with a unique ability to capture speed, color and noise through the medium of a still photograph, often eschewing the obvious in favor of the abstract Formula 1 is the aesthete's ultimate sport: an intoxicating cocktail of speed, spectacle, competition and power, at the heart of which are the thoroughbred racing machines - exquisite manifestations of form following function, driven at dizzying speeds by the quickest-of-the-quick, the best racing drivers on the planet. Darren Heath has been photographing Formula 1 for over 25 years. For 21 of these years he has worked freelance, and this has given him a unique perspective on the complex and exciting world of Formula 1. Darren Heath's photography in Art of The Race V17 encapsulates the very essence of the speed, noise, excitement and color of Formula 1 racing, whilst also highlighting the key moments of each race as the season unfolds, culminating in Lewis Hamilton winning his 4th world championship.

* 256 pages of stunning photography, including 234 pages of full color* This is the sixth volume in Darren Heath's Art of the Race series; a legend among Formula 1 photographers, now in his 31st year covering the sport* Very active on social media with a cult following among Formula 1 fans* The Formula One book.Art of the Race, V19 is book six in a series that encapsulates the very essence of Formula 1 motor racing through the lens of Darren Heath, one of the sport's greatest ever photographers. Across 256 pages of stunning photography, Art of the Race, V19 captures the key moments and rarely seen images of each race as the 2019 season unfolds, culminating in Lewis Hamilton winning his sixth World title. And there is no person better placed to capture these moments than Darren Heath, a multiple award-winning photographer and Honorary Fellow of The Royal Photographic Society, who is now in his 31st year covering the sport.

* Art Of The Race is Darren Heath's first photography book, and is book 1 in a series of collaborations with Art Of Publishing Limited* Darren Heath is one of the preeminent photographers in F1 today, with a unique ability to capture speed, color and noise through the medium of a still photograph, often eschewing the obvious in favor of the abstract; he has 46,000 Twitter followers* Formula One is a global sport with an affluent and loyal fanbaseSpeed, color, noise, excitement. Art Of The Race, V14 encapsulates the very essence of Formula 1 motor racing through the lens of Darren Heath, one of the sport's most celebrated photographers. Art Of The Race captures the key moments and rarely seen footage of each race as the season unfolds, whether it's the epic battle between Mclaren teammates Hamilton and Rosberg, or the humbling drivers' gathering in support of their colleague Jules Bianchi.

Book three in a series celebrating the phenomenon of street art in the world's greatest cities. A photographer's view of Rio De Janeiro's transient street art scene. Celebrating the vibrancy, creativity and colour of the movement and documenting a time and place in its history. Artist's work include Wark Rocinha, NATA, Vida One Love, MEMI, Cranio and Panmela Castro with many more both celebrated and unknown. These books show the colour, detail and skill in these works, showcasing the talents of these contemporary artists.

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.