Other books that might interest you

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  Mastering Blockchain - Unlocking...

  Daniel Cawrey, Lorne Lantz

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  The future will be increasingly distributed. As the publicity surrounding Bitcoin and blockchain has shown, distributed technology and business models are gaining popularity. Yet the disruptive potential of this technology is often obscured by hype and misconception. This detailed guide distills the complex, fast moving ideas behind blockchain into an easily digestible reference manual, showing what's really going on under the hood. 
   
   
   
  Finance and technology pros will learn how a blockchain works as they explore the evolution and current state of the technology, including the functions of cryptocurrencies and smart contracts. This book is for anyone evaluating whether to invest time in the cryptocurrency and blockchain industry. Go beyond buzzwords and see what the technology really has to offer. 
   
   
   
  In this book, you'll learn why Bitcoin was fundamentally important in blockchain's birth; how Ethereum has created a fertile ground for new innovations like Decentralized Finance, Non-Fungible Tokens, and Flash Loans; how cryptocurrencies are used by criminals to carry out nefarious activities; and how enterprise and governments are leveraging the blockchain. You'll also discover the challenges of scaling and forking a blockchain; find out how different blockchains work; and learn the language of blockchain as industry terms are explained.

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  Perpendicular Times - A New Reality

  Michael Mathiesen

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  In previous books, I have put forth a new theory of time - in that time flows about the universe in waves. This has not been proven yet, but I'm confident it will be some day since everything else in the universe flows or comes out of wave energy - the odds are very good that time does as well. 
  Since announcing this theory a couple years ago in a book called 'Time Waves', I also saw that time not only flows about the universe in waves, but that these waves flow at right angles or in a perpendiular orientation to all other waves because they, time waves, carry the elements of time that all other waves require to be a wave. The two fields interact in perpendicular fashion to create what Einstein calls Space/Time, but now it comes along with a completely new and more complete definition. 
  But, it's also part of my theory that artificial intelligence is here at this time to play an important role so I asked Orac, my long-time AI assistant to confirm that my theory is accurate and he does in great detail. It's an historic moment for all and holds significant impacts on all our lives.

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  overview of An: Cancer as a...

  Dr. Thomas Seyfried, Dr. Dominic...

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  25% of the royalties of this book will be donated to Dr. Seyfrieds research (See KetoforCancer.net)! This research will actually make a real impact, as it studies the real causes and treatment opportunities of cancer. 
  This book is an overview of Dr. Thomas Seyfrieds scientific work, regarding that Cancer is a metabolic disease. It comprisesTranscripts of his talks and interviews that summarize all his most important points, as well asA Presentation by his collegue Dr. Dominic D'Agostiono about the "Press Pulse Strategy" andA possible way of eating, that would prevent cancer from the get go: The RockSolid Diet (by J.Rockermeier) 
  Here the description of his scientific work: 
  "Cancer as a metabolic disease" addresses controversies related to the origins of cancer and provides solutions to cancer management and prevention. It expands upon Otto Warburg's well-known theory that all cancer is a disease of energy metabolism. However, Warburg did not link his theory to the "hallmarks of cancer" and thus his theory was discredited.This book aims to provide evidence, through case studies, that cancer is primarily a metabolic disease requring metabolic solutions for its management and prevention. 
  Brain cancer case studies are presented as a proof of principle for metabolic solutions to disease management, but similarities are drawn to other types of cancer, including breast and colon, due to the same cellular mutations that they demonstrate. 
  This book comprises the opinion of Dr. Thomas Seyfried regarding the metabolic nature of cancer. He states, that it is not genetic, but a mitochondrial disease. 
  This book is NOT a summary of his original, scientific book. It's rather a collection of video transcripts, that summarize his point. With official permission, because we donate 25% of the royalties directly to his research!

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  The Origin of Humankind

  Richard Leakey

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  "The name Leakey is synonymous with the study of human origins," wrote The New York Times. The renowned family of paleontologists-Louis Leakey, Mary Leakey, and their son Richard Leakey-has vastly expanded our understanding of human evolution. The Origin of Humankind is Richard Leakey's personal view of the development of Homo Sapiens. At the heart of his new picture of evolution is the introduction of a heretical notion: once the first apes walked upright, the evolution of modern humans became possible and perhaps inevitable. From this one evolutionary step comes all the other evolutionary refinements and distinctions that set the human race apart from the apes. In fascinating sections on how and why modern humans developed a social organization, culture, and personal behavior, Leakey has much of interest to say about the development of art, language, and human consciousness.

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  Reaching the Moon: The History...

  Editors Charles River

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  The Apollo Program is the most famous and celebrated in American history, but the first successful landing of men on the Moon during Apollo 11 had complicated roots dating back over a decade, and it also involved one of NASA’s most infamous tragedies. From 1959-1963, the United States worked toward putting satellites and humans into orbit via the Mercury program, but Eisenhower’s administration was already designing plans for the Apollo program by 1960, a year before the first Russian orbited the Earth and two years before John Glenn became the first American to orbit the Earth. 
  At the same time, America would begin missions to the Moon as early as 1958. On March 27, 1958, Secretary of Defense Neil McElroy announced a lunar project for the International Geophysical Year, consisting of three Air Force launches followed by two Army launches of a JPL-designed lunar probe. ARPA directed the Air Force to launch its probes "as soon as possible consistent with the requirement that a minimal amount of useful data concerning the Moon be obtained." 
  Throughout the 1960s, NASA would spend tens of billions on missions to the Moon, the most expensive peacetime program in American history to that point, and Apollo was only made possible by the tests conducted through earlier missions, including the historic Ranger Program. Conceived as an early part of the attempt to land a man on the Moon, Ranger was designed to photograph the lunar surface in preparation for future landings. Until Ranger, images of the Moon were only available through Earth-based telescopes, which lacked the detail necessary to determine safe sites for landing a spacecraft. Ranger aimed to fill in that gap of knowledge, and like many of NASA’s missions during the 1960s, the program exemplified both the successes and the failures of the agency’s early years.

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  Machine Learning with Python -...

  Alexander Cane

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  Ways to combat retraining depend on the algorithm and consist of the correct values of the trainer's met parameters. In practice, model estimation is not performed on the same input data that was used to train the model. Divide 10-20% of all available data into a separate set and call it a set for evaluation. We will bring the other 10-20% into the set for ratification, and 60-80% of the remaining ones will be given to the trainer. The principle of data sharing depends on the data and the task. Random sampling is often a good method if inputs are independent of each other, and there is no strong imbalance between the number of positive and negative entries. 
  The intuitive analogy here is the same as with university studies: the teacher solves some problems with students in pairs and gives other’s similar tasks in the exam. What is important here (both in teaching students and models) is that these tasks are varied, and students cannot simply memorize the answers, and those who have mastered the material (similar tasks) will be able to repeat the thought process and answer correctly. 
  In machine learning, we split into data two sets: we will use the evaluation set to evaluate each model we train, using different approaches, algorithms, and model types to select the best one. That is, for each model, we will have two precision values - precision on the training dataset and precision on the evaluation dataset. It is normal for the former to be higher than the second, but not significantly. A big difference indicates retraining.

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