Comet For Data Science
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Comet for Data Science
Gain the key knowledge and skills required to manage data science projects using Comet Key Features: Discover techniques to build, monitor, and optimize your data science projects Move from prototyping to production using Comet and DevOps tools Get to grips with the Comet experimentation platform Book Description: This book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model. The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You'll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available. By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet. What You Will Learn: Prepare for your project with the right data Understand the purposes of different machine learning algorithms Get up and running with Comet to manage and monitor your pipelines Understand how Comet works and how to get the most out of it See how you can use Comet for machine learning Discover how to integrate Comet with GitLab Work with Comet for NLP, deep learning, and time series analysis Who this book is for: This book is for anyone who has programming experience, and wants to learn how to manage and optimize a complete data science lifecycle using Comet and other DevOps platforms. Although an understanding of basic data science concepts and programming concepts is needed, no prior knowledge of Comet and DevOps is required.
Comets III
Author: Karen J Meech
language: en
Publisher: University of Arizona Press
Release Date: 2024
Comets III brings together the major breakthroughs in comet science over the last twenty years. Edited by experts in the field, this comprehensive volume explores recent advancements in space missions, telescopic observations, and robotic surveys, providing new understandings of the composition, origins and dynamics of comets. Intended for both researchers and students, Comets III offers insights into unresolved questions and sets the stage for future advancements.
Physics and Chemistry of Comets
Author: Walter F. Huebner
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
As this excellent book demonstrates, the study of comets has now reached the fas cinating stage where we understand comets in general simple tenns while, at the same time, we are uncertain about practically all the details of cometary nature, structure, processes, and origin. In every aspect, even including dynamics, a choice among several or many competing theories is made impossible simply by the lack of detailed knowledge. The space missions, snapshot studies of two comets, partic ularly the one that immortalizes the name of Sir Edmund Halley, have produced a huge mass of valuable new infonnation and a number of surprises. Nonetheless, we face the tantalizing realization that we have obtained only a fleeting glance at two of perhaps a hundred billion (lOll) or more comets with possibly differing natures, origins, and physical histories. To my personal satisfaction, comets seem to have discrete nuclei made up of dirty snowballs, as I concluded four decades ago, but perhaps they are more like frozen rubbish piles.