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Orland Bishop is a remarkable man who has combined extensive study of medicine, naturopathy, psychology and indigenous cosmologies with a deep dedication to human rights, Founder of the ShadeTree foundation which works with at-risk young people in Los Angeles, Bishop's primary work is around supporting individuals to be open to the higher purpose of their lives.In this fascinating book he reveals the influences on his life and work, in particular the spiritual tradition of African Gnosis, and significant individuals from the history of the African experience in America.Drawing on anthroposophy and other spiritual traditions, he explores the nature of the soul journey, and the quest for community and prosperity.
For Cal Hewitt, the expectations of his family are paramount. For Eric Hamilton, life is an adventure to be experienced. These opposing world views lead Cal and Eric in opposite directions. Outland, the author of the bestseller "Every Man for Himself, " has created a heartfelt valentine to the notion that love comes quietly and in the most unlikely ways.
The Land of Orland dates from the pre-Gold Rush 1840s when Granville Perry Swift selected the area for the adobe headquarters of his vast cattle operation. The naming of the town took place in 1875 when three men--who could not agree on a name--put their choices on slips of paper and the name "Orland" was drawn from the hat. Orland saw a great influx of development in the 1910s with the completion of the Orland Irrigation Project" the first federally funded irrigation project on the West Coast. With water available at reasonable prices, small dairies and orchards sprang up around the town. Promotional efforts brought new families into the community. Vintage photographs from these "good old days" give a lasting picture of Orland's agricultural heritage.
In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks