Matt Jackson – författare

The electric and daring independent wrestling tag team share their inspiring story of how two undersized, ambitious athletes from Southern California became the idols of millions of popular sports fans, coveted among the ranks of AEW’s elite wrestling lineup. Featuring over 60 photographs and alternating between each brother’s perspective, this entertaining memoir is a complete portrait of what it means to grow into—and give back to—wrestling, the sport and profession they embody and love.Famous for their highflying moves, Superkicks, and viral videos, Matt and Nick Jackson are two of the hottest and most talented competitors in professional wrestling today. Known as the Young Bucks, this pair of ambitious brothers are an inspiration to both fans and aspiring wrestlers worldwide due to their message of resilience and determination. That they are also faithful family men devoted to their loved ones gives them additional appeal.Young Bucks begins in Southern California, where two young boys grew up dreaming of success and fame. Matt and Nick look back on the sacrifices they made to achieve their ambitions, from taking odd jobs to pay for their own wrestling ring to hosting backyard events with friends. They share their joy at being recruited into the independent California wrestling circuit and the work it took to finally make it professionally, and speak frankly about what it means to have the support of millions of fans cheering their talents in arenas nationwide. The Young Bucks talk endearingly about their sport, their faith, and their families, sharing personal reflections and behind-the-scenes anecdotes while paying tribute to the wrestling acts and inspirations that came before them. They also elaborate on this historical time in the evolution of wrestling, as the sport and its culture dramatically change day by day.Told with the brothers’ signature wit and charm, Young Bucks is warm, heartfelt story of hope, perseverance, and undying ambition.

Learn how to transform, store, evolve, refactor, model, and create graph projections using the Python programming language Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesTransform relational data models into graph data model while learning key applications along the wayDiscover common challenges in graph modeling and analysis, and learn how to overcome themPractice real-world use cases of community detection, knowledge graph, and recommendation networkBook DescriptionGraphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you’ll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis.Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you’ll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you’ll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you’ll also get to grips with adapting your network model to evolving data requirements.By the end of this book, you’ll be able to transform tabular data into powerful graph data models. In essence, you’ll build your knowledge from beginner to advanced-level practitioner in no time.What you will learnDesign graph data models and master schema design best practicesWork with the NetworkX and igraph frameworks in Python Store, query, ingest, and refactor graph dataStore your graphs in memory with Neo4jBuild and work with projections and put them into practiceRefactor schemas and learn tactics for managing an evolved graph data modelWho this book is forIf you are a data analyst or database developer interested in learning graph databases and how to curate and extract data from them, this is the book for you. It is also beneficial for data scientists and Python developers looking to get started with graph data modeling. Although knowledge of Python is assumed, no prior experience in graph data modeling theory and techniques is required.