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    https://sophisticatedspectra.com/article/drosia-serenity-a-modern-oasis-in-the-heart-of-larnaca.2521391.html

    DROSIA SERENITY
    A Premium Residential Project in the Heart of Drosia, Larnaca

    ONLY TWO FLATS REMAIN!

    Modern and impressive architectural design with high-quality finishes Spacious 2-bedroom apartments with two verandas and smart layouts Penthouse units with private rooftop gardens of up to 63 m² Private covered parking for each apartment Exceptionally quiet location just 5–8 minutes from the marina, Finikoudes Beach, Metropolis Mall, and city center Quick access to all major routes and the highway Boutique-style building with only 8 apartments High-spec technical features including A/C provisions, solar water heater, and photovoltaic system setup.
    Drosia Serenity is not only an architectural gem but also a highly attractive investment opportunity. Located in the desirable residential area of Drosia, Larnaca, this modern development offers 5–7% annual rental yield, making it an ideal choice for investors seeking stable and lucrative returns in Cyprus' dynamic real estate market. Feel free to check the location on Google Maps.
    Whether for living or investment, this is a rare opportunity in a strategic and desirable location.

    Learn Amazon SageMaker: A guide to building, training, and deploying machine learning models for developers, 2nd Edition

    Posted By: yoyoloit
    Learn Amazon SageMaker: A guide to building, training, and deploying machine learning models for developers, 2nd Edition

    Learn Amazon SageMaker
    by Julien Simon

    English | 2021 | ISBN: ‎ 1801817952 | 554 pages | True PDF EPUB | 62.16 MB

    Swiftly build and deploy machine learning models without managing infrastructure and boost productivity using the latest Amazon SageMaker capabilities such as Studio, Autopilot, Data Wrangler, Pipelines, and Feature Store
    Key Features

    Build, train, and deploy machine learning models quickly using Amazon SageMaker
    Optimize the accuracy, cost, and fairness of your models
    Create and automate end-to-end machine learning workflows on Amazon Web Services (AWS)

    Book Description

    Amazon SageMaker enables you to quickly build, train, and deploy machine learning models at scale without managing any infrastructure. It helps you focus on the machine learning problem at hand and deploy high-quality models by eliminating the heavy lifting typically involved in each step of the ML process. This second edition will help data scientists and ML developers to explore new features such as SageMaker Data Wrangler, Pipelines, Clarify, Feature Store, and much more.

    You'll start by learning how to use various capabilities of SageMaker as a single toolset to solve ML challenges and progress to cover features such as AutoML, built-in algorithms and frameworks, and writing your own code and algorithms to build ML models. The book will then show you how to integrate Amazon SageMaker with popular deep learning libraries, such as TensorFlow and PyTorch, to extend the capabilities of existing models. You'll also see how automating your workflows can help you get to production faster with minimum effort and at a lower cost. Finally, you'll explore SageMaker Debugger and SageMaker Model Monitor to detect quality issues in training and production.

    By the end of this Amazon book, you'll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation.
    What you will learn

    Become well-versed with data annotation and preparation techniques
    Use AutoML features to build and train machine learning models with AutoPilot
    Create models using built-in algorithms and frameworks and your own code
    Train computer vision and natural language processing (NLP) models using real-world examples
    Cover training techniques for scaling, model optimization, model debugging, and cost optimization
    Automate deployment tasks in a variety of configurations using SDK and several automation tools

    Who this book is for

    This book is for software engineers, machine learning developers, data scientists, and AWS users who are new to using Amazon SageMaker and want to build high-quality machine learning models without worrying about infrastructure. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. A solid understanding of machine learning concepts and the Python programming language will also be beneficial.