Machine Learning with Python

Design patterns are proven solutions to common problems in development. If you've ever found yourself constantly writing the same thing when creating objects or struggling with managing different types of objects, then the factory pattern might be exactly what you need.

In this tutorial:
https://www.freecodecamp.org/news/how-to-use-the-factory-pattern-in-python-a-practical-guide/

you'll learn what a factory is, why it's useful, and how to implement it in #Python. We'll gather practical examples that will show when and how to apply this pattern in real tasks.

The code can be found on #GitHub
https://github.com/balapriyac/python-basics/tree/main/design-patterns/factory

https://t.me/CodeProgrammer

These 9 lectures from Stanford are a pure goldmine for anyone wanting to learn and understand LLMs in depth

Lecture 1 - Transformer: https://lnkd.in/dGnQW39t

Lecture 2 - Transformer-Based Models & Tricks: https://lnkd.in/dT_VEpVH

Lecture 3 - Tranformers & Large Language Models: https://lnkd.in/dwjjpjaP

Lecture 4 - LLM Training: https://lnkd.in/dSi_xCEN

Lecture 5 - LLM tuning: https://lnkd.in/dUK5djpB

Lecture 6 - LLM Reasoning: https://lnkd.in/dAGQTNAM

Lecture 7 - Agentic LLMs: https://lnkd.in/dWD4j7vm

Lecture 8 - LLM Evaluation: https://lnkd.in/ddxE5zvb

Lecture 9 - Recap & Current Trends: https://lnkd.in/dGsTd8jN

Start understanding #LLMs in depth from the experts. Go through each step-by-step video.

https://t.me/DataAnalyticsX 🔗

teach Transformer.

Register Free:
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https://t.me/CodeProgrammer

🐱 5 of the Best GitHub Repos
🔃 for Data Scientists

👨🏻‍💻 When I was just starting out and trying to get into the "data" field, I had no one to guide me, nor did I know what exactly I should study. To be honest, I was confused for months and felt lost.

▶️ But doing projects was like water on fire and helped me a lot to build my skills.

〰 Repo Awesome Data Analysis

🏷 A complete treasure trove of everything you need to start: SQL, Python, AI, data analysis, and more... In short, if you want to start from zero and strengthen your foundation, start here first.

                   ➖ ➖ ➖

〰 Repo Data Scientist Handbook

🏷 A concise handbook that tells you what you need to learn and what you can ignore for now.

                   ➖ ➖ ➖

〰 Repo Cookiecutter Data Science

🏷 A standard project template used by professionals. With this template, you can structure your data analysis and AI projects like a pro.

                   ➖ ➖ ➖

〰 Repo Data Science Cookie Cutter

🏷 This is also a very clean project template that teaches you how to build a data project that won’t fall apart tomorrow and can be easily updated. Meaning your projects will be useful in the real world from the start.

                   ➖ ➖ ➖

〰 Repo ML From Scratch

🏷 Here, the main AI algorithms are implemented from scratch in simple language. It’s great for understanding how models really work and for explaining them well in your interviews.

🌐 #Data_Science #DataScience

Master Python together with the University of Helsinki

• get an official certificate after completion
• go from complete beginner to confident level
• 14 intensive modules with practical tasks

The course is waiting for you here
https://programming-25.mooc.fi/

Neural Networks: How They Learn and Predict

https://t.me/CodeProgrammer

https://t.me/RAICompass

مبادرة جميلة يرجى الانضمام اليها - للسوريين (مبادرة هامة) 🇸🇾

9 key concepts of artificial intelligence, explained in 7 minutes

- Tokenization
- #TextDecoding
- #PromptEngineering
- Multi Step #AI Agents
- #RAGs
- #RLHF
- #VAE
- #DiffusionModels
- #LoRA

👉 @Python53

This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://t.me/addlist/8_rRW2scgfRhOTc0

✅ https://t.me/Codeprogrammer

AI Developers — finally something serious.

A German company 🇩🇪 (Brainlancer GmbH) is launching a curated B2B platform on April 1st, 2026.

Not a freelance marketplace.
Not an agency network.
A verified AI builder network.

Only a few spots are still open.

If you can actually ship outcomes like:
• RAG / Agents in production
• Automations + API integrations
• FastAPI tools, internal apps, backend systems

→ apply now (free + anonymous).
http://assesment.brainlancer.com/?src=telegram

Step 1: 5 min form
Step 2: 15–20 min AI interview
Step 3: short call → early access

👉 Brainlancer.com (Landingpage)
👉 https://www.linkedin.com/in/soner-catakli/ (CEO)

#KMeans clustering animation in the style of 3blue1brown

👉 @CODEPROGRAMMER

nature papers: 1200$

Q1 and  Q2 papers    700$

Q3 and Q4 papers   400$

Doctoral thesis (complete)    600$

M.S thesis         300$

paper simulation   200$

Contact @Omidyzd62

NumPy Cheat Sheet: Data Analysis in Python

This #Python cheat sheet is a quick reference for #NumPy beginners.

Learn more:
https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python

https://t.me/DataAnalyticsX

Machine Learning with Python pinned a photo

🧠 Converting images to ASCII: text instead of pixels

Want to turn any image into ASCII art? It's not magic, just simple brightness processing.

It's tedious and stupid to do it manually
img = [
    [255, 0, 0],
    [0, 255, 0]
]
# Now we need to pick a symbol for each pixel...
# What a hassle.

Problem:
Manually selecting symbols by brightness is a pain. We need to automate the conversion of grayscale to symbols.

✔️ The right way (using gradation)

from PIL import Image

def image_to_ascii(path, width=100):
    img = Image.open(path)
    aspect = img.height / img.width
    height = int(width * aspect * 0.55)
    img = img.resize((width, height)).convert('L')

    ascii_chars = '@%#*+=-:. '
    pixels = img.getdata()

    ascii_art = '\n'.join(
        ascii_chars[pixel * (len(ascii_chars) - 1) // 255]
        for pixel in pixels
    )
    lines = [ascii_art[i:i+width] for i in range(0, len(ascii_art), width)]
    return '\n'.join(lines)

print(image_to_ascii('cat.jpg'))

How it works:
convert('L') converts the image to grayscale

Each pixel (0-255) is assigned a symbol from the set

The darker the pixel, the "denser" the symbol (e.g., '@'), the lighter - the "weaker" (space)

Let's write a converter with customizable palette:

class AsciiConverter:
    PALETTES = {
        'default&#39: '@%#*+=-:. ',
        'blocks&#39: '█rayed ',
        'detailed&#39: '$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\\|()1{}[]?-_+~<>i!lI;:,"^`\'. '
    }

    def __init__(self, palette_name='default&#39):
        if palette_name not in self.PALETTES:
            raise ValueError(f'Нет такой палитры, идиот. Выбери из: {list(self.PALETTES.keys())}')
        self.chars = self.PALETTES[palette_name]

    def convert(self, image_path, width=80):
        # ... code to convert using self.chars ...
        return ascii_result

Try specifying a non-existent palette - you'll get a clear error.

Key parameters:

🔵Width - determines the size of the final ASCII art
🔵Character palette - affects the detail and style
🔵Aspect ratio - important for correct display
🔵Inversion - you can invert the brightness for a dark background

Important:
ASCII art isn't just a fun thing. It's used to visualize data in the console, create creative logs, and even "hide" information in plain sight.

👩‍💻 @CodeProgrammer

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Here's the full path I would recommend to build production-grade AI agents this year:

▪️a foundation in Python and algorithms
▪️mathematics and the basics of ML
▪️transformers and LLMs
▪️prompt engineering
▪️memory and RAG
▪️tools and integrations
▪️frameworks like LangChain or CrewAI
▪️multi-agent systems
▪️testing, deployment, and security

👉 @Codeprogrammer

free

Learn Python with the University of Helsinki

✓ With an official certificate
✓ From zero to advanced level
✓ 14 parts with practical tasks

All content is available → here
https://programming-25.mooc.fi/

👉 @codeprogrammer

GitHub has launched its learning platform: all #courses and certificates in one place.

#Git, #GitHub, #MCP, using #AI, #VSCode, and much more.

And most of the content is #free: → https://learn.github.com

👉 @codeprogrammer