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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.

    Introduction to Machine Learning with Python: A Guide for Data Scientists

    Posted By: IrGens
    Introduction to Machine Learning with Python: A Guide for Data Scientists

    Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Müller, Sarah Guido
    English | October 21, 2016 | ASIN: B01M0LNE8C, ISBN: 1449369413 | AZW3 | 400 pages | 13.6 MB

    Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.

    You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.

    With this book, you’ll learn:

    Fundamental concepts and applications of machine learning
    Advantages and shortcomings of widely used machine learning algorithms
    How to represent data processed by machine learning, including which data aspects to focus on
    Advanced methods for model evaluation and parameter tuning
    The concept of pipelines for chaining models and encapsulating your workflow
    Methods for working with text data, including text-specific processing techniques
    Suggestions for improving your machine learning and data science skills