Machine Learning with Python

“Learn AI” is everywhere. But where do the builders actually start? Here’s the real path, the courses, papers and repos that matter. ✅ Videos: Everything here ⇒ https://lnkd.in/ePfB8_rk ➡️ LLM Introduction → https://lnkd.in/ernZFpvB ➡️ LLMs from Scratch - Stanford CS229 → https://lnkd.in/etUh6_mn ➡️ Agentic AI Overview →https://lnkd.in/ecpmzAyq ➡️ Building and Evaluating Agents → https://lnkd.in/e5KFeZGW ➡️ Building Effective Agents → https://lnkd.in/eqxvBg79 ➡️ Building Agents with MCP → https://lnkd.in/eZd2ym2K ➡️ Building an Agent from Scratch → https://lnkd.in/eiZahJGn ✅ Courses: All Courses here ⇒ https://lnkd.in/eKKs9ves ➡️ HuggingFace's Agent Course → https://lnkd.in/e7dUTYuE ➡️ MCP with Anthropic → https://lnkd.in/eMEnkCPP ➡️ Building Vector DB with Pinecone → https://lnkd.in/eP2tMGVs ➡️ Vector DB from Embeddings to Apps → https://lnkd.in/eP2tMGVs ➡️ Agent Memory → https://lnkd.in/egC8h9_Z ➡️ Building and Evaluating RAG apps → https://lnkd.in/ewy3sApa ➡️ Building Browser Agents → https://lnkd.in/ewy3sApa ➡️ LLMOps → https://lnkd.in/ex4xnE8t ➡️ Evaluating AI Agents → https://lnkd.in/eBkTNTGW ➡️ Computer Use with Anthropic → https://lnkd.in/ebHUc-ZU ➡️ Multi-Agent Use → https://lnkd.in/e4f4HtkR ➡️ Improving LLM Accuracy → https://lnkd.in/eVUXGT4M ➡️ Agent Design Patterns → https://lnkd.in/euhUq3W9 ➡️ Multi Agent Systems → https://lnkd.in/evBnavk9 ✅ Guides: Access all ⇒ https://lnkd.in/e-GA-HRh ➡️ Google's Agent → https://lnkd.in/encAzwKf ➡️ Google's Agent Companion → https://lnkd.in/e3-XtYKg ➡️ Building Effective Agents by Anthropic → https://lnkd.in/egifJ_wJ ➡️ Claude Code Best practices → https://lnkd.in/eJnqfQju ➡️ OpenAI's Practical Guide to Building Agents → https://lnkd.in/e-GA-HRh ✅ Repos: ➡️ GenAI Agents → https://lnkd.in/eAscvs_i ➡️ Microsoft's AI Agents for Beginners → https://lnkd.in/d59MVgic ➡️ Prompt Engineering Guide → https://lnkd.in/ewsbFwrP ➡️ AI Agent Papers → https://lnkd.in/esMHrxJX ✅ Papers: 🟡 ReAct → https://lnkd.in/eZ-Z-WFb 🟡 Generative Agents → https://lnkd.in/eDAeSEAq 🟡 Toolformer → https://lnkd.in/e_Vcz5K9 🟡 Chain-of-Thought Prompting → https://lnkd.in/eRCT_Xwq 🟡 Tree of Thoughts → https://lnkd.in/eiadYm8S 🟡 Reflexion → https://lnkd.in/eggND2rZ 🟡 Retrieval-Augmented Generation Survey → https://lnkd.in/eARbqdYE Access all ⇒ https://lnkd.in/e-GA-HRh By: https://t.me/CodeProgrammer 🟡

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Python Cheat Sheet (very very important) 📖 Compact Python cheat sheet covering setup, syntax, data types, variables, strings, control flow, functions, classes, errors, and I/O. Link: https://discord.com/channels/942740928706281524/1423994784720359567/1424711790947864669

Big surprise in our channels on Discord https://discord.gg/PGZku7DrSz

📌 Missing Value Imputation, Explained: A Visual Guide with Code Examples for Beginners 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-08-27 | ⏱️ Read time: 13 min read One (tiny) dataset, six imputation methods?

Great find for developers: free cheat sheets on Deep Learning and PyTorch A detailed guide to creating and training neural networks - link Basic principles and practice of working with PyTorch - link 👉 @CODEPROGRAMMER

Awesome interactive textbook on probability theory and statistics Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works Get it here, I recommend opening it on a desktop https://seeing-theory.brown.edu/ 👉 @DataScienceM

📌 Extracting Structured Vehicle Data from Images 🗂 Category: 🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read Build an Automated Vehicle Documentation System that Extracts Structured Information from Images, using OpenAI API,…

Awesome interactive textbook on probability theory and statistics Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works Get it here, I recommend opening it on a desktop https://seeing-theory.brown.edu/ 👉 @DataScienceM

Awesome interactive textbook on probability theory and statistics Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works Get it here, I recommend opening it on a desktop https://seeing-theory.brown.edu/ 👉 @DataScienceM I spent years chasing success until I found the 7 daily habits no one talks about—now everything’s changed for me. Most people miss the real secret. See what you’ve been overlooking: Success Tips 🔥 | InsideAds

📌 How to Build a Genetic Algorithm from Scratch in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-30 | ⏱️ Read time: 16 min read A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…

Python library RetinaFace for face detection and working with key points (eyes, nose, mouth) Supports face alignment, easily installed via pip install retina-face, and works based on deep models from the insightface project. An excellent tool for tasks in computer vision and face recognition. Usage examples:

from retinaface import RetinaFace

resp = RetinaFace.detect_faces("img1.jpg")
print(resp)

{
    "face_1": {
        "score": 0.9993440508842468,
        "facial_area": [155, 81, 434, 443],
        "landmarks": {
          "right_eye": [257.82974, 209.64787],
          "left_eye": [374.93427, 251.78687],
          "nose": [303.4773, 299.91144],
          "mouth_right": [228.37329, 338.73193],
          "mouth_left": [320.21982, 374.58798]
        }
  }
}

👉 @DataScienceN

Creating QR codes with Python in just a few lines of code Anyone can generate their own QR code for a link, text, or even Wi-Fi data. For this, the qrcode library and the PIL module are used

pip install qrcode pillow

import qrcode
from PIL import Image

data = input("Enter data for QR: ")
qr = qrcode.QRCode(version=3, box_size=8, border=4)
qr.add_data(data)
qr.make(fit=True)

image = qr.make_image(fill="black", back_color="aqua")
image.save("qr_code.png")
Image.open("qr_code.png")

The output is a ready QR code with any text or link. You can change colors, sizes, and style to fit your design 🙂 👉 https://t.me/CodeProgrammer

📌 A Guide to Clustering Algorithms 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read An overview of clustering and the different families of clustering algorithms.

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📌 Image Segmentation With K-Means Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read An introduction with Python

Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role prompting to advanced techniques like few-shot learning, avoiding hallucinations, and tool use. Perfect interactive lessons to level up your AI skills Link: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P