Tradutor Alexander Teixeira de Mattos
Editora: e-artnow
This natural history book focuses entirely on the life cycle of different caterpillars, beginning with egg-laying. Fabre was a famous entomologist who wrote many works about insects.
Our nation's transportation system is crumbling. But as acclaimed scholar and ACLU president Deborah Archer warns in Dividing Lines, before we can think about rebuilding and repairing, we must consider the role race has played in transportation infrastructure, from the early twentieth century and into the present day. As Archer demonstrates, the success of the Civil Rights movement and the fall of Jim Crow in the 1960s did not mean the end of segregation. With state-sanctioned racism no longer legal, officials across the country turned to transportation infrastructure to keep Americans divided. A wealthy white neighborhood could no longer be "protected" by racial covenants and segregated shops, but a multilane road, with no pedestrian crossings, could be built along its border to make it difficult for people from a lower-income community to visit. Highways could not be routed through Black neighborhoods based on the race of their residents, but those neighborhoods' lower property values—a legacy of racial exclusion—could justify their destruction. Drawing on a wealth of sources, including interviews with people who now live in the shadow of highways and other major infrastructure projects, Archer presents a sweeping, national account—from Atlanta and Houston to Indianapolis and New York City—of our persistent divisions.Ver livro
Take a data-first and use-case-driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data; feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to distinguish between structured and unstructured data and the challenges they present; visualize and analyze data; preprocess data for input into a machine learning model; differentiate between the regression and classification supervised learning models; compare different ML model types and architectures, from no code to low code to custom training; design, implement, and tune ML models; and export data to a GitHub repository for data management and governance.Ver livro
Dark matter is one of the most elusive and mysterious components of the universe. Though it cannot be directly observed through traditional means such as light, it is believed to make up about 27% of the universe's total mass and energy content. This strange substance does not emit, absorb, or reflect light, making it invisible to our telescopes and detectors. Its existence is inferred primarily through its gravitational effects on visible matter, such as galaxies and galaxy clusters. Without dark matter, the movement of galaxies would not make sense based on the gravitational pull of visible matter alone. The concept of dark matter was first proposed in the early 20th century. In 1933, Swiss astronomer Fritz Zwicky observed that the galaxies within the Coma galaxy cluster were moving faster than expected based on the visible matter alone. He suggested that there must be some unseen mass, which he called “dark matter,” providing the additional gravitational pull needed to keep the galaxies from flying apart. Since then, astronomers have found similar evidence in other galaxy clusters, and the hypothesis of dark matter has become a cornerstone of modern cosmology. Despite the compelling evidence for dark matter, its exact nature remains unknown. Various theories have been proposed, with the most widely accepted one suggesting that dark matter consists of weakly interacting massive particles, or WIMPs. These hypothetical particles would interact through gravity and possibly the weak nuclear force, but not through electromagnetic forces, which would explain why they do not emit light. However, despite decades of searching, no direct detection of WIMPs has been made. This has led to the consideration of alternative explanations, such as axions, sterile neutrinos, and other exotic particles.Ver livro
When Derek Yu released Spelunky for free in 2008, his roguelike-inspired platformer took the indie game community by storm with its combination of classic platform mechanics, extreme difficulty, and random level generation. Four years later, Spelunky's HD remake went on to become PC Gamer's Game of the Year and earn perfect scores from Polygon and Eurogamer. But how is a "perfect" game made? Spelunky is Boss Fight's first autobiographical book: the story of a game's creation as told by its creator. Using his own game as a vehicle, Derek Yu discusses such wide-ranging topics as randomization, challenge, indifferent game worlds, player feedback, development team dynamics, and what's required to actually finish a game. Grab some ropes, a mattock, and your favorite pug—this book is going to dig deep.Ver livro
Revolutionize your marketing strategies and outperform traditional practices with the power of AI. Elevate your marketing game and achieve unprecedented success with "The AI Marketing Revolution," a comprehensive 420-page guide by Vitalij Kolotikov. This book has been successfully adopted by libraries of leading universities in London, Paris, and Riga, making it an essential resource for students and professionals. Whether you're an entrepreneur or a student aiming to master both traditional and AI-driven marketing strategies, this book provides you with the knowledge and tools to optimize your marketing efforts, increase sales, and secure your dream job as a marketing expert. Discover how to leverage AI to transform your marketing landscape and stay ahead in an ever-evolving digital world.Ver livro
In an era where IT environments are growing more complex and dynamic, traditional monitoring and management approaches can no longer keep up. AIOps: Automating IT Operations with Artificial Intelligence explores how artificial intelligence and machine learning are revolutionizing the way organizations manage, optimize, and future-proof their IT operations. This book offers a practical and strategic introduction to AIOps (Artificial Intelligence for IT Operations), providing readers with a deep understanding of how AI-driven tools can detect anomalies, predict outages, automate root cause analysis, and deliver real-time insights across hybrid infrastructures. From reducing noise in alert systems to enabling proactive incident resolution, AIOps empowers IT teams to shift from reactive firefighting to intelligent, automated operations. This guide helps you harness the full potential of AIOps to improve system reliability, accelerate response times, and enhance business agility.Ver livro
