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Python Data Science jobs, interview tips, and career insights for aspiring professionals.

Admin: @HusseinSheikho || @Hussein_Sheikho
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πŸ”¬Python 3.14: What's New? πŸ“ˆ

⏰ In 2025, a wave of developer-focused improvements arrived with Python 3.14. Let's dive into some exciting new features:

β€’ Lazy annotations resolve long-standing type hinting quirks
β€’ Clever t-strings give more control over string interpolation

These enhancements solidify Python's position as the language of choice for AI-powered development.

πŸ“š Stay up-to-date with the latest Python news and advancements in 2026! #Python #MachineLearning
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πŸ”₯ Generating fake data in Python β€” no pain at all

If you're testing forms, mockups, or just want to play with data, there's Mimesis β€” a generator of fake data. Names, emails, addresses, and phone numbers. There's a location setting that allows you to select a country, and the data will be generated accordingly.

πŸ“¦ Installation:
from typing import Dict
from mimesis.enums import Gender
from mimesis import Person

def generate_fake_user(locale: str = "es", gender: Gender = Gender.MALE) -> Dict[str, str]:
    """
    Generates fake user data based on the locale and gender.

    :param locale: The locale (for example, 'ru', 'en', 'es')
    :param gender: The gender (Gender.MALE or Gender.FEMALE)
    :return: A dictionary with the fake user data
    """
    person = Person(locale)

    user_data = {
        "name": person.full_name(gender=gender),
        "height": person.height(),
        "phone": person.telephone(),
        "occupation": person.occupation(),
    }

    return user_data

if __name__ == "__main__":
    fake_user = generate_fake_user(locale="es", gender=Gender.MALE)
    print(fake_user)


πŸ“Œ Result:
{
  'name': 'Carlos Herrera',
  'height': '1.84',
  'phone': '912 475 289',
  'occupation': 'Arquitecto'
)


⚑️ Mimesis can:
πŸ–± Generate names, addresses, phone numbers, professions, etc. 
πŸ–± Work with different countries (πŸ‡·πŸ‡Ί ru, πŸ‡ΊπŸ‡Έ en, πŸ‡ͺπŸ‡Έ es, etc.) 
πŸ–± Suitable for tests, fake accounts, demo data in projects, and bots.

βš™οΈ GitHub/Instructions

Save it, it'll come in handy πŸ‘

#python #github #interview
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πŸ‘ A fresh deep learning course from MIT is now available publicly

A full-fledged educational course has been published on the university's website: 24 lectures, practical tasks, homework assignments, and a collection of materials for self-study.

The program includes modern neural network architectures, generative models, transformers, inference, and other key topics.

A great opportunity to study deep learning based on the structure of a top university, free of charge and without simplifications β€” let's learn here.
https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/resources/lecture-videos/

tags: #python #deeplearning

➑ @codeprogrammer
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πŸ”– An excellent resource for learning about neural networks

We're sharing a cool resource for learning about neural networks, offering clear, step-by-step instruction with dynamic visualizations and easy-to-understand explanations.

In addition, you'll find many other useful materials on machine learning on the site.

Find and use it β€” https://mlu-explain.github.io/neural-networks/

tags: #AI #ML #PYTHON

➑ @CODEPROGRAMMER
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Build and Automate Django CRM

#Django #CRM #PYTHON
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