A Complete Course to Learn Robotics and Perception

Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson

github.com/gtbook/robotics

roboticsbook.org/intro.html

#Robotics #Perception #AI #DeepLearning #ComputerVision #RoboticsCourse #MachineLearning #Education #RoboticsResearch #GitHub

⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟

💻 GHOSTCREW — A Python AI tool for penetration testers and security professionals that conducts vulnerability searches in any services.

It works like a red team within your system. You describe the task in plain language — then it plans the attack itself, selects tools, and proceeds through the entire process: from reconnaissance to reporting. Without manual fiddling and endless commands.

What it can do in practice:
➡️ Checks everything: code, business logic, network traffic, protocols.
➡️ Analyzes the found vulnerabilities and explains where the problem is and how to fix it.
➡️ Works autonomously — you just launch it and get a full-fledged research.
➡️ Connects MCP servers and tools (nmap, metasploit, ffuf, etc.) itself.
➡️ Uses Pentesting Task Trees for meaningful decision-making, not just brute force.
➡️ Supports ready-made workflows for comprehensive checks.
➡️ Generates detailed reports in Markdown with facts and recommendations.
➡️ Remembers the dialogue context and doesn't "get lost" after a couple of requests.
➡️ Sees real files: wordlists, payloads, configs — and uses them in its work.
➡️ Allows you to choose an AI model and customize its behavior.
➡️ No registration and no restrictions.

⚙️ Installation:

git clone https://github.com/GH05TCREW/ghostcrew.git
cd ghostcrew
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

▶️ Usage:

python main.py

⚠️ The information is provided solely for informational purposes. And it encourages to pay attention to security issues.

♎️ GitHub/Instructions

#python #soft #github

😰 A repository of more than 100+ ready-made Python scripts that solve a bunch of tasks - without reinventing the wheel and suffering at night.

💬 parsing and searching on the internet;
💬 working with photos and videos;
💬 keyloggers and password managers;
💬 cloning websites;
💬 automating routines;
💬 and dozens of other useful things for real cases.

🔥 Ready-made practice + code, suitable for both learning and work.

⬇️ Save it, it will definitely come in handy!

#python #soft #github

🔥 Generating fake data in Python — no pain at all

If you're testing forms, mockups, or just want to play with data, there's Mimesis — 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.

📦 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)

📌 Result:

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

⚡️ Mimesis can:
🖱 Generate names, addresses, phone numbers, professions, etc. 
🖱 Work with different countries (🇷🇺 ru, 🇺🇸 en, 🇪🇸 es, etc.) 
🖱 Suitable for tests, fake accounts, demo data in projects, and bots.

⚙️ GitHub/Instructions

Save it, it'll come in handy 👍

#python #github #interview