No bullshit guide to math and physics
Ivan Savov - 2010
It shouldn't be like that. Learning calculus without mechanics is incredibly boring. Learning mechanics without calculus is missing the point. This textbook integrates both subjects and highlights the profound connections between them.This is the deal. Give me 350 pages of your attention, and I'll teach you everything you need to know about functions, limits, derivatives, integrals, vectors, forces, and accelerations. This book is the only math book you'll need for the first semester of undergraduate studies in science.With concise, jargon-free lessons on topics in math and physics, each section covers one concept at the level required for a first-year university course. Anyone can pick up this book and become proficient in calculus and mechanics, regardless of their mathematical background.Visit http://minireference.com for more details.
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
David Marr - 1982
A computational investigation into the human representation and processing of visual information.
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Pedro Domingos - 2015
In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.
How to Predict the Unpredictable: The Art of Outsmarting Almost Everyone
William Poundstone - 2014
We chase ‘winning streaks’ that are often just illusions, and we are all too predictable exactly when we try hardest not to be.In the 1970s, Daniel Kahneman and Amos Tversky coined the phrase ‘representativeness’ to describe the psychology of this behaviour. Since then representativeness has been used by auditors to catch people fiddling their tax returns and by hedge fund managers to reap billions from the emotions of small investors. Now Poundstone for the first time makes these techniques fun, easy, and profitable for everyone, in the everyday situations that matter. You’ll learn how to tackle multiple choice tests, what internet passwords to avoid, how to up your odds of winning the office Premier League sweepstakes, and the best ways to invest your money.
Introducing philosophy
Open University - 2016
This 8-hour free course introduced the study of philosophy and the methods employed by The Open University in teaching philosophy.
Deep Learning with Python
François Chollet - 2017
It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.
Prince Andrew: The End of the Monarchy and Epstein
Nigel Cawthorne - 2020
But few know the palace intrigue behind their long-standing triangular relationship. Going behind the headlines, documentaries and mini-series, PRINCE ANDREW exposes for the first time the unknown details of the Epstein scandal behind secretive palace gates and how it impacted on the power struggle between Andrew and his older brother Prince Charles.Rife with machinations and plots, it paints a rare and riveting, insider picture of vice and rarified daily life at the royal court. It is an unbelievable story how a boy from Coney Island befriended the world's foremost royal family. PRINCE ANDREW casts a truly eye-watering light on one of the dirtiest stories of our time, giving the reader much-needed forensic insight into all the facts, allegations and counter-allegations.
Day Trading Made Easy: A Simple Strategy for Day Trading Stocks
Matthew R. Kratter - 2017
Amazon best-selling author and professional trader, Matthew Kratter will teach you everything you need to know to day trade stocks-- and to avoid getting wiped out. And if you ever get stuck, you can always reach out to him by email (provided inside of the book), and he will help you. To start making money today, scroll to the top of this page and click BUY NOW.
Mathematical Circles: Russian Experience (Mathematical World, Vol. 7)
Dmitri Fomin - 1996
The work is predicated on the idea that studying mathematics can generate the same enthusiasm as playing a team sport - without necessarily being competitive.
Data Mining: Practical Machine Learning Tools and Techniques
Ian H. Witten - 1999
This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915 0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
Tiny Blunders/Big Disasters: Thirty-Nine Tiny Mistakes That Changed the World Forever (Revised Edition)
Jared Knott - 2020
World History
Design and Analysis of Experiments
Douglas C. Montgomery - 1976
Douglas Montgomery arms readers with the most effective approach for learning how to design, conduct, and analyze experiments that optimize performance in products and processes. He shows how to use statistically designed experiments to obtain information for characterization and optimization of systems, improve manufacturing processes, and design and develop new processes and products. You will also learn how to evaluate material alternatives in product design, improve the field performance, reliability, and manufacturing aspects of products, and conduct experiments effectively and efficiently. Discover how to improve the quality and efficiency of working systems with this highly-acclaimed book. This 6th Edition: Places a strong focus on the use of the computer, providing output from two software products: Minitab and DesignExpert. Presents timely, new examples as well as expanded coverage on adding runs to a fractional factorial to de-alias effects. Includes detailed discussions on how computers are currently used in the analysis and design of experiments. Offers new material on a number of important topics, including follow-up experimentation and split-plot design. Focuses even more sharply on factorial and fractional factorial design.
Schaum's Outline of Differential Equations
Richard Bronson - 2006
Thoroughly updated, this edition offers new, faster techniques for solving differential equations generated by the emergence of high-speed computers.
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
Peter Dayan - 2001
This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.
Lectures on the Foundations of Mathematics, Cambridge 1939
Ludwig Wittgenstein - 1989
A lecture class taught by Wittgenstein, however, hardly resembled a lecture. He sat on a chair in the middle of the room, with some of the class sitting in chairs, some on the floor. He never used notes. He paused frequently, sometimes for several minutes, while he puzzled out a problem. He often asked his listeners questions and reacted to their replies. Many meetings were largely conversation. These lectures were attended by, among others, D. A. T. Gasking, J. N. Findlay, Stephen Toulmin, Alan Turing, G. H. von Wright, R. G. Bosanquet, Norman Malcolm, Rush Rhees, and Yorick Smythies. Notes taken by these last four are the basis for the thirty-one lectures in this book. The lectures covered such topics as the nature of mathematics, the distinctions between mathematical and everyday languages, the truth of mathematical propositions, consistency and contradiction in formal systems, the logicism of Frege and Russell, Platonism, identity, negation, and necessary truth. The mathematical examples used are nearly always elementary.