Amazon Notebook Cover
Download Amazon Notebook Cover PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Amazon Notebook Cover book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Amazon Ink
The first in a thrilling series from the USA TODAY bestselling author of the Nine Worlds series following an Amazonian woman in modern-day Wisconsin as she struggles to solve two mysterious and shocking murders. It’s been ten years since Melanippe Saka left her Amazon tribe in order to create a normal life for her daughter Harmony. True, running a tattoo parlor in Madison, Wisconsin, while living with your Amazon warrior mother and priestess grandmother is not everyone’s idea of normal, but Mel thinks she’s succeeded at blending in as human. Turns out she’s wrong. Someone knows all about her, someone who’s targeting young Amazonian girls, and no way is Mel going to let Harmony become tangled in this deadly web. With her motherly instinct in overdrive, Ms. Melanippe Saka is quite a force…even when she’s facing a barrage of distractions—including a persistent detective whose interest in Mel goes beyond professional, a sexy tattoo artist with secrets of his own, and a seriously angry Amazon queen who views Mel as a prime suspect. To find answers, Mel will have to do the one thing she swore she’d never do: embrace her powers and admit that you can take the girl out of the tribe...but you can’t take the tribe out of the girl.
Amazon SageMaker Best Practices
Author: Sireesha Muppala
language: en
Publisher: Packt Publishing Ltd
Release Date: 2021-09-24
Overcome advanced challenges in building end-to-end ML solutions by leveraging the capabilities of Amazon SageMaker for developing and integrating ML models into production Key FeaturesLearn best practices for all phases of building machine learning solutions - from data preparation to monitoring models in productionAutomate end-to-end machine learning workflows with Amazon SageMaker and related AWSDesign, architect, and operate machine learning workloads in the AWS CloudBook Description Amazon SageMaker is a fully managed AWS service that provides the ability to build, train, deploy, and monitor machine learning models. The book begins with a high-level overview of Amazon SageMaker capabilities that map to the various phases of the machine learning process to help set the right foundation. You'll learn efficient tactics to address data science challenges such as processing data at scale, data preparation, connecting to big data pipelines, identifying data bias, running A/B tests, and model explainability using Amazon SageMaker. As you advance, you'll understand how you can tackle the challenge of training at scale, including how to use large data sets while saving costs, monitoring training resources to identify bottlenecks, speeding up long training jobs, and tracking multiple models trained for a common goal. Moving ahead, you'll find out how you can integrate Amazon SageMaker with other AWS to build reliable, cost-optimized, and automated machine learning applications. In addition to this, you'll build ML pipelines integrated with MLOps principles and apply best practices to build secure and performant solutions. By the end of the book, you'll confidently be able to apply Amazon SageMaker's wide range of capabilities to the full spectrum of machine learning workflows. What you will learnPerform data bias detection with AWS Data Wrangler and SageMaker ClarifySpeed up data processing with SageMaker Feature StoreOvercome labeling bias with SageMaker Ground TruthImprove training time with the monitoring and profiling capabilities of SageMaker DebuggerAddress the challenge of model deployment automation with CI/CD using the SageMaker model registryExplore SageMaker Neo for model optimizationImplement data and model quality monitoring with Amazon Model MonitorImprove training time and reduce costs with SageMaker data and model parallelismWho this book is for This book is for expert data scientists responsible for building machine learning applications using Amazon SageMaker. Working knowledge of Amazon SageMaker, machine learning, deep learning, and experience using Jupyter Notebooks and Python is expected. Basic knowledge of AWS related to data, security, and monitoring will help you make the most of the book.
Selected Amazon Reviews
A book-length selection from Kevin Killian's legendary corpus of more than two thousand product reviews posted on Amazon.com. An enchanting roll of duct tape. Love Actually on Blu-ray Disc. The Toaster Oven Cookbook, The Biography of Stevie Nicks, and an anthology of poets who died of AIDS. In this only book-length selection from his legendary corpus of more than two thousand product reviews posted on Amazon.com, sagacious shopper Kevin Killian holds forth on these household essentials and many, many, many others. The beloved author of more than a dozen volumes of innovative poetry, fiction, drama, and scholarship, Killian was for decades a charismatic participant in San Francisco’s New Narrative writing circle. From 2003–2019, he was also one of Amazon’s most prolific reviewers, rising to rarefied “Top 100” and “Hall of Fame” status on the site. Alternately hilarious and heartfelt, Killian’s commentaries consider an incredible variety of items, each review a literary escapade hidden in plain sight amongst the retailer’s endless pages of user-generated content. Selected Amazon Reviews at last gathers an appropriately wide swath of this material between two covers, revealing the project to be a unified whole and always more than a lark. Some for “verified purchases,” others for products enjoyed in theory, Killian’s reviews draw on the influential strategies of New Narrative, his unrivaled fandom for both elevated and popular culture, and the fine art of fabulation. Many of them are ingeniously funny—flash-fictional riffs on the commodity as talismanic object, written by a cast of personas worthy of Pessoa. And many others are serious, even scholarly—earnest tributes to contemporaries, and to small-press books that may not have received attention elsewhere, offered with exemplary attention. All of Killian’s reviews subvert the Amazon platform, queering it to his own play with language, identity, genre, critique. Killian’s prose is a consistent pleasure throughout Selected Amazon Reviews, brimming with wit, lyricism, and true affection. As the Hall of Famer himself reflected on this form-of-his-own-invention shortly before his untimely passing in 2019: “They’re reviews of a sort, but they also seem like novels. They’re poems. They’re essays about life. I get a lot of my kinks out there, on Amazon.”