Tags
Language
Tags
July 2025
Su Mo Tu We Th Fr Sa
29 30 1 2 3 4 5
6 7 8 9 10 11 12
13 14 15 16 17 18 19
20 21 22 23 24 25 26
27 28 29 30 31 1 2
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    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.

    Beginning with Machine Learning & Data Science in Python

    Posted By: Sigha
    Beginning with Machine Learning & Data Science in Python

    Beginning with Machine Learning & Data Science in Python
    .MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | 542 MB
    Duration: 3.5 hours | Genre: eLearning Video | Language: English

    Fundamentals of Data Science : Exploratory Data Analysis (EDA), Regression (Linear & logistic), Visualization, Basic ML.

    What you'll learn

    You will be able to apply data science algorithms for solving industry problems
    You will have a clear understanding of industry standards and best practices for predictive model building
    You will be able to derive key insights from data using exploratory data analysis techniques
    You will be able to efficiently handle data in a structured way using Pandas
    You will have a strong foundation of linear regression, multiple regression and logistic regression
    You will be able to use python scikit-learn for building different types of regression models
    You will be able to use cross validation techniques for comparing models, select parameters
    You will know about common pitfalls in modeling like over-fitting, bias-variance trade off etc..
    You will be able to regularize models for reliable predictions

    Requirements

    Basic programming in any language
    Basic Mathematics
    Some exposure to Python (but not mandatory)

    Description
    85% of data science problems are solved using exploratory data analysis (EDA), visualization, regression (linear & logistic). Naturally, 85% of the interview questions comes from these topics as well.

    This is a concise course created by UNP to focus on what matter most. This course will help you create a solid foundation of the essential topics of data science. With a solid foundation, you will be able to go a long way, understand any method easily, and create your own predictive analytics models.

    At the end of this course, you will be able to:

    Get your hands dirty by building machine learning models

    Master logistic and linear regression, the workhorse of data science

    Build your foundation for data science

    Fast-paced course with all the basic & intermediate level concepts

    Learn to manage data using standard tools like Pandas

    This course is designed to get students on board with data science and make them ready to solve industry problems. This course is a perfect blend of foundations of data science, industry standards, broader understanding of machine learning and practical applications.

    Special emphasis is given to regression analysis. Linear and logistic regression is still the workhorse of data science. These two topics are the most basic machine learning techniques that everyone should understand very well. Concepts of over fitting, regularization etc. are discussed in details. These fundamental understandings are crucial as these can be applied to almost every machine learning methods.

    This course also provide an understanding of the industry standards, best practices for formulating, applying and maintaining data driven solutions. It starts off with basic explanation of Machine Learning concepts and how to setup your environment. Next data wrangling and EDA with Pandas are discussed with hands on examples. Next linear and logistic regression is discussed in details and applied to solve real industry problems. Learning the industry standard best practices and evaluating the models for sustained development comes next.

    Final learning are around some of the core challenges and how to tackle them in an industry setup. This course supplies in-depth content that put the theory into practice.

    Who this course is for:

    Anyone willing to take the first step towards data science
    Anyone willing to develop a solid foundation for data science
    Anyone planning to build the first regression / machine learning models
    Anyone willing to learn exploratory data analysis

    Beginning with Machine Learning & Data Science in Python