Aaron Jones – författare

In AD79, the volcano Mount Vesuvius unleashed its terrifying wrath upon the cities of Prompeii and Herculaneum, and the smaller towns in its domain around, smothering them from the face of the earth with its spitting fires of molten pumice, deadly burning showers of ash, and rivers of red-hot lava.Many tales and stories led toward this tragic event. One such tale was of a certain slave; a mean brought to Rome in chains, to entertain as a gladiator, to reluctantly kill his fellow man in the bloody arenas of the Roman world. But fate was to take him into conflicting fortunes; into strange, volatile destinies; that was to lead eventually to his involvement with the terrible catastrophe of Vesuvius.Such a man was Caradawg; a prodigious, fearless man, from the mountainous regions of the island province of Britannia. A slave who became a demigod.He was known to the Romans, as CARACTACUS.

From the Wolds of the West, across the Seas of Lorth, came the long elf, Gyral. In wild and unfrequented realms he sought for truth and enlightenment of the mysteries of his world, a treacherous world infested with strange and evil life-forms, ferocious predators, riddled with countless perils. But for Gyral, curiosity was far more powerful than the fears that confronted him. Curiosity was his addiction; knowledge was his quest. He had heard of the great immortal city, the citadel of mystery and foreboding. It was the fabulous infamous city all outsiders feared to enter. Yet the bold wayfarer became obsessed by its existence; thus he sought to find it. On his far journeys, he would confront all evil obstacles, encounter the wizards of science, the wondrous characters, wild and weird communities. He visited the inns and taverns, braved the deep forests, and he relished the damsels. But he knew he must one day find and behold the phenomenon, thence brazenly enter into the citadel of Bilbabalbabul.

This book I have written, which I titled We Do Learn the Things We Learn, is a collection of poems written to express how we, as human beings, learn love for each other through our relationships, both good and bad. I hope the reader will feel what I felt as I was writing the collection, the feelings coming from my heart to theirs, because, as the title says, we do learn the things we learn.

Learning how to apply unsupervised algorithms on unlabeled datasets from scratch can be easier than you thought with this beginner's workshop, featuring interesting examples and activitiesKey FeaturesGet familiar with the ecosystem of unsupervised algorithmsLearn interesting methods to simplify large amounts of unorganized dataTackle real-world challenges, such as estimating the population density of a geographical areaBook DescriptionDo you find it difficult to understand how popular companies like WhatsApp and Amazon find valuable insights from large amounts of unorganized data? The Unsupervised Learning Workshop will give you the confidence to deal with cluttered and unlabeled datasets, using unsupervised algorithms in an easy and interactive manner.The book starts by introducing the most popular clustering algorithms of unsupervised learning. You'll find out how hierarchical clustering differs from k-means, along with understanding how to apply DBSCAN to highly complex and noisy data. Moving ahead, you'll use autoencoders for efficient data encoding.As you progress, you’ll use t-SNE models to extract high-dimensional information into a lower dimension for better visualization, in addition to working with topic modeling for implementing natural language processing (NLP). In later chapters, you’ll find key relationships between customers and businesses using Market Basket Analysis, before going on to use Hotspot Analysis for estimating the population density of an area.By the end of this book, you’ll be equipped with the skills you need to apply unsupervised algorithms on cluttered datasets to find useful patterns and insights.What you will learnDistinguish between hierarchical clustering and the k-means algorithmUnderstand the process of finding clusters in dataGrasp interesting techniques to reduce the size of dataUse autoencoders to decode dataExtract text from a large collection of documents using topic modelingCreate a bag-of-words model using the CountVectorizerWho this book is forIf you are a data scientist who is just getting started and want to learn how to implement machine learning algorithms to build predictive models, then this book is for you. To expedite the learning process, a solid understanding of the Python programming language is recommended, as you’ll be editing classes and functions instead of creating them from scratch.