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Linspired
No athletic scholarships, ignored by the NBA draft, waived by team after team, yet Jeremy Lin remained positive and never doubted God’s plan. Finally picked up by the New York Knicks, a teammate’s injury placed Lin on the court after weeks on the bench. Since then, Lin has captivated the sports world with his incredible basketball skills as a New York Knick and now a Houston Rocket. This is his remarkable story.
Linspired, Kids Edition
Linspired reveals the inside story of the remarkable and meteoric rise of Jeremy Lin, superstar of the New York Knicks the first Asian-American-born player of Chinese/Taiwanese descent to play in the NBA. Discover the journey of the underdog who beat the odds to reach his current stardom and catch the attention of the sports world with both his incredible basketball skills and his on and off-court example of faith, persistence, and hard work. After receiving no athletic scholarship offers out of high school and not being drafted by an NBA team after graduating from Harvard, Lin signed a deal with his hometown team of the Golden State Warriors. After only his first year of play he was waived by the Warriors, but he was picked up by the Houston Rockets. Again, he was let go, on Christmas Eve, 2011. In spite of this disappointment, Lin always remained positive and trusted that God had a plan for his life and talents. Soon after, Lin was picked up when the New York Knicks needed a guard. After weeks of sitting on the bench, a teammate’s injury placed Lin on the court, and since then he has captivated sports fans throughout the world with his tremendous skill and humble response.
Calculus for Machine Learning
Calculus seems to be obscure, but it is everywhere. In machine learning, while we rarely write code on differentiation or integration, the algorithms we use have theoretical roots in calculus. If you ever wondered how to understand the calculus part when you listen to people explaining the theory behind a machine learning algorithm, this new Ebook, in the friendly Machine Learning Mastery style that you’re used to, is all you need. Using clear explanations and step-by-step tutorial lessons, you will understand the concept of calculus, how it is relates to machine learning, what it can help us on, and much more.
The Churchman
None
A Conceptual Model for the Integrated Policy Framework
In the Mundell-Fleming framework, standard monetary policy and exchange rate flexibility fully insulate economies from shocks. However, that framework abstracts from many real world imperfections, and countries often resort to unconventional policies to cope with shocks, such as COVID-19. This paper develops a model of optimal monetary policy, capital controls, foreign exchange intervention, and macroprudential policy. It incorporates many shocks and allows countries to differ across the currency of trade invoicing, degree of currency mismatches, tightness of external and domestic borrowing constraints, and depth of foreign exchange markets. The analysis maps these shocks and country characteristics to optimal policies, and yields several principles. If an additional instrument becomes available, it should not necessarily be deployed because it may not be the right tool to address the imperfection at hand. The use of a new instrument can lead to more or less use of others as instruments interact in non-trivial ways.
Piv And Water Waves
This volume introduces particle image velocimetry (PIV), a technique for water wave measurement in the laboratory and in the open ocean. It discusses the turbulent dissipation, Reynolds stresses and vortical structures in boundary layers of the sea bed, as well as ships, ship wakes, propulsion hydrodynamics, cavitation and free surface waves. Upwelling behind crests of micro-breaking ocean surface waves (important for the exchange of greenhouse gases between air and water) and large amplitude internal solitons in the ocean are measured. The book includes velocities and accelerations in breaking ocean waves, run-up, interaction between strong waves and breakwaters, as well as a concise descri...
Coding with ChatGPT and Other LLMs
Leverage LLM (large language models) for developing unmatched coding skills, solving complex problems faster, and implementing AI responsibly Key Features Understand the strengths and weaknesses of LLM-powered software for enhancing performance while minimizing potential issues Grasp the ethical considerations, biases, and legal aspects of LLM-generated code for responsible AI usage Boost your coding speed and improve quality with IDE integration Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionKeeping up with the AI revolution and its application in coding can be challenging, but with guidance from AI and ML expert Dr. Vincent Hall—who holds a PhD in machine ...
Mechanics of the 21st Century
This volume contains the proceedings of the 21st International Congress of Theoretical and Applied Mechanics, ICTAM04, held in Warsaw, in August 2004. Full texts of 27 invited lectures are included. The book captures a snapshot view of the state-of-the-art in the field of contemporary mechanics and will be invaluable to engineers and scientists from a variety of disciplines with interest in the mechanical sciences. The importance of the influence of contemporary mechanics on other branches of sciences becomes evident by browsing through over 60 areas of interest selected as subjects of mini-symposia and pre-nominated sessions. The book gives clear evidence that "...the progress we have achieved together definitely places mechanics on one of the very top locations in the hierarchy of modern research disciplines – with tremendous impact on both our perception of the physical world and the means to implement new technologies so much improving the quality of our life." (M. Kleiber, Opening Speech).
Optimization for Machine Learning
Optimization happens everywhere. Machine learning is one example of such and gradient descent is probably the most famous algorithm for performing optimization. Optimization means to find the best value of some function or model. That can be the maximum or the minimum according to some metric. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will learn how to find the optimum point to numerical functions confidently using modern optimization algorithms.
