Tag: Optimal

Prompt Engineering – For Optimal LLM Performance


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MP4 | Video: h264, 1920X1080| Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 1h 2m | Size: 508 MB
Prompt engineering is key to harnessing the immense capabilities of large language models. In this in-depth masterclass, data and AI specialist Valentina Alto unveils the art and science behind crafting effective prompts. You’ll learn proven techniques to optimize prompting, control model behavior, reduce risks like hallucination, and overcome limitations. Valentina provides specific strategies to make your LLMs more precise, aligned to your goals, and production ready. With her deep expertise and hands-on guidance, you’ll be able to create prompts that act as precise instructions enabling your large language models to deliver peak performance. This masterclass equips you with prompt engineering skills to build conversative AI applications that leverage the full potential of LLMs.

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Build Optimal Models with Azure Automated ML


Free Download Build Optimal Models with Azure Automated ML
Axel Sirota | Duration: 1:15 h | Video: H264 1280×720 | Audio: AAC 48 kHz 2ch | 639 MB | Language: English
Regardless of if you have some hours or some years building models, Azures’s Automated Machine Learning has something to amaze you. This course will teach you how to use it to build the best Machine Learning model for your data in just a few clicks!
Building Machine Learning models means iterating multiple times over the best features, the best architectures, the best algorithms, until you get a model that serves your business purpose. In this course, Build Optimal Models with Azure Automated ML, you’ll learn to create the best machine learning model for your own specific data in just a few clicks. First, you’ll explore what Auto ML really is. Next, you’ll discover how to create optimal models both from the UI as well as the SDK. Finally, you’ll learn how to improve our models with more advanced techniques Azure ML offers. When you’re finished with this course, you’ll have the skills and knowledge of Automated Machine Learning needed to build the best Machine Learning model for your data in just a few clicks!
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The Optimal Design of Blocked and Split-Description Experiments


Free Download The Optimal Design of Blocked and Split-Description Experiments by Peter Goos
English | PDF (True) | 2002 | 256 Pages | ISBN : 0387955151 | 19.6 MB
Quality has become an important source of competitive advantage for the modern company. Therefore, quality control has become one of its key ac tivities. Since the control of existing products and processes only allows moderate quality improvements, the optimal design of new products and processes has become extremely important. This is because the flexibility, which characterizes the design stage, allows the quality to be built in prod ucts and processes. In this way, substantial quality improvements can be achieved. An indispensable technique in the design stage of a product or a process is the statistically designed experiment for investigating the effect of sev eral factors on a quality characteristic. A number of standard experimental designs like, for instance, the factorial designs and the central compos ite designs have been proposed. Although these designs possess excellent properties, they can seldom be used in practice. One reason is that using standard designs requires a large number of observations and can therefore be expensive or time-consuming. Moreover, standard experimental designs cannot be used when both quantitative and qualitative factors are to be in vestigated or when the factor levels are subject to one or more constraints.

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M-Statistics Optimal Statistical Inference for a Small Sample


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by Demidenko, Eugene;

English | 2023 | ISBN: 1119891795 | 240 pages | True EPUB/pdf | 16.51/8 MB
M-STATISTICS A comprehensive resource providing new statistical methodologies and demonstrating how new approaches work for applications M-statistics introduces a new approach to statistical inference, redesigning the fundamentals of statistics, and improving on the classical methods we already use. This book targets exact optimal statistical inference for a small sample under one methodological umbrella. Two competing approaches are maximum concentration (MC) and mode (MO) statistics combined under one methodological umbrella, which is why the symbolic equation M=MC+MO. M-statistics defines an estimator as the limit point of the MC or MO exact optimal confidence interval when the confidence level approaches zero, the MC and MO estimator, respectively. Neither mean nor variance plays a role in M-statistics theory. Novel statistical methodologies in the form of double-sided unbiased and short confidence intervals and tests apply to major statistical Our new developments are accompanied by respective algorithms and R codes, available at GitHub, and as such readily available for applications. M-statistics is suitable for professionals and students alike. It is highly useful for theoretical statisticians and teachers, researchers, and data science analysts as an alternative to classical and approximate statistical inference.

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Optimal Illusions The False Promise of Optimization [Audiobook]


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English | ASIN: B0BWQ7LZMN | 2023 | 6 hours and 30 minutes | M4B@128 kbps | 362 MB
Author: Coco Krumme
Narrator: Coco Krumme

How optimization took over the world and the urgent case for a new approach. Optimization is the driving principle of our modern world. We now can manufacture, transport, and organize things more cheaply and faster than ever. Optimized models underlie everything from airline schedules to dating site matches. We strive for efficiency in our daily lives, obsessed with productivity and optimal performance. How did a mathematical concept take on such outsize cultural shape? And what is lost when efficiency is gained?

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Reinforcement Learning Optimal Feedback Control with Industrial Applications


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English | 2023 | ISBN: 3031283937 | 539 Pages | PDF EPUB (True) | 49 MB
This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems.

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Optimal Transport A Semi-discrete Approach


Free Download Gershon Wolansky, "Optimal Transport: A Semi-discrete Approach "
English | ISBN: 3110633124 | 2021 | 262 pages | EPUB | 27 MB
The series is devoted to the publication of high-level monographs which cover the whole spectrum of current nonlinear analysis and applications in various fields, such as optimization, control theory, systems theory, mechanics, engineering, and other sciences. One of its main objectives is to make available to the professional community expositions of results and foundations of methods that play an important role in both the theory and applications of nonlinear analysis. Contributions which are on the borderline of nonlinear analysis and related fields and which stimulate further research at the crossroads of these areas are particularly welcome.

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Optimal Control From Variations to Nanosatellites


Free Download Adam B Levy, "Optimal Control: From Variations to Nanosatellites "
English | ISBN: 3111289834 | 2023 | 176 pages | EPUB, PDF | 15 MB + 25 MB
This book may serve as a basis for students and teachers. The text should provide the reader with a quick overview of the basics for Optimal Control and the link with some important conceptes of applied mathematical, where an agent controls underlying dynamics to find the strategy optimizing some quantity. There are broad applications for optimal control across the natural and social sciences, and the finale to this text is an invitation to read current research on one such application. The balance of the text will prepare the reader to gain a solid understanding of the current research they read.

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