🚀 𝟲𝟬 𝗗𝗮𝘆𝘀 𝗼𝗳 𝗖𝗼𝗱𝗶𝗻𝗴 | 𝗗𝗦𝗔 𝘅 𝗥𝗲𝗮𝗹 𝗪𝗼𝗿𝗹𝗱 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 #Day40 | 𝗚𝗿𝗮𝗽𝗵 𝗥𝗲𝘃𝗶𝘀𝗶𝗼𝗻 𝗮𝗻𝗱 𝗔𝗣𝗜 𝗘𝗻𝗮𝗯𝗹𝗲𝗺𝗲𝗻𝘁 Revisited graph fundamentals and refactored traversal logic into service-oriented design to reflect real backend usage. Focused on: • BFS and DFS revision • Reusable graph services • Clean abstraction • Bridging DSA with system design thinking 📌 𝗖𝗼𝗱𝗲 𝗮𝗻𝗱 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: https://lnkd.in/gxzGJ4nB Feedback and suggestions are welcome. #DSA #Graphs #SystemDesign #Python #60DaysOfCoding #LearningInPublic #SoftwareEngineering

RAG APIs: Moving from basic endpoints to AI-driven search. ⚡ While most are still stuck in manual API setup, I’ve been leveraging FastAPI to build a RAG (Retrieval-Augmented Generation) system that turns static documents into a searchable intelligence layer. The Tech Stack: 🔹 FastAPI: High-performance, asynchronous Python framework. 🔹 ChromaDB: Vector store for semantic document retrieval. 🔹 Ollama: Local LLMs for private, efficient inference. 🔹 Swagger UI: Instant, interactive documentation for seamless hand-offs. Key Wins: ✅ Production-ready AI integration. ✅ Automated documentation (no more "how do I call this?" questions). ✅ Fully local, scalable vector search. Huge thanks to @NextWork for the project framework. Full technical breakdown here: 👉 https://lnkd.in/gvrDiekX #FastAPI #RAG #AI #Python #DevOps #NextWork #SoftwareEngineering

AI generated code has a reusability issue and every new task means starting from scratch. In CODED FLOWS, when you use AI to generate code, it becomes a reusable Python component as a visual node in your workflow. You can drag it around, connect it to other nodes, use it in different projects. We also let you generate Streamlit pages canvas directly in the UI editor. This demo shows how this works in practice.

🚀 Day 41 of #100DaysofCode Challenge! Today’s focus was on recursion and backtracking patterns: 🔹 Generate Parentheses Solved this using a backtracking approach by building valid combinations incrementally while maintaining two constraints: The number of opening brackets used must not exceed n The number of closing brackets must not exceed the number of opening brackets This ensures only valid sequences are generated without checking invalid ones afterward. Core idea: Use recursion to explore all valid states Add '(' if openings < n Add ')' if closings < openings Key takeaways: ✔ Backtracking with constraint pruning ✔ Recursive state-space exploration ✔ Understanding how valid combinations grow systematically Time Complexity: O(4ⁿ / √n) (related to Catalan numbers) Space Complexity: O(n) for recursion stack Building stronger intuition for recursion and combinatorial problems every day 🚀 📸 Screenshots of solution are attached! #Day41 #DynamicProgramming #BinaryTree #TreeDP #Algorithms #ProblemSolving #Python #Java #CodingMindset #SoftwareEngineering #AdityaVerma #CodingJourney

AI Web Designer that generates complete HTML websites directly inside a Python notebook and renders them. The demo is built with Mercury and shows how notebooks can go beyond experiments - the AI writes pure HTML, the page is previewed instantly, and the source code is visible side by side. Notebook code https://lnkd.in/dpA45rn9

Augmented Assignment Operators Augmented assignments, which combine an operation and an assignment into a single, concise step. - Augmented assignments follow the format variable <operator>= value, offering a cleaner alternative to writing variable = variable <operator> value. - Explored commonly used operators such as +=, -=, *=, /=, //=, %=, and **= for numeric calculations. - Learned how these operators improve readability, reduce repetition, and help avoid errors caused by retyping variable names. - Practiced using augmented assignments with strings for example, += for concatenation and *= for repetition while understanding why other operators raise Type error. - Noted that Python intentionally avoids ++ and -- operators, encouraging explicit updates like x += 1 for clarity. #Python #AugmentedAssignment #PythonForDataAnalytics #LearningInPublic #Upskilling

Project Launches MCP Server to Power AI Image Generation Workflows 📌 A new Python-based MCP server is revolutionizing AI image generation by enabling seamless integration with tools like Claude Desktop/Code. Modular and efficient, it supports batch processing, multiple image quality tiers, and automated format conversion, making it a powerful addition to creative workflows. Open-source and customizable, it empowers developers to enhance AI-driven image creation with ease. 🔗 Read more: https://lnkd.in/dSD-5cZW #Mcpserver #Python #Aiimagegeneration #Jsonrpc2 #Modulararchitecture

Today I focused on Python functions Functions aren’t just about writing code. They’re about: ▪️ Breaking problems into smaller pieces ▪️ Making logic reusable ▪️ Keeping systems clean and maintainable When thinking ahead to GenAI systems and LLM workflows, modular thinking becomes very important. Agents, tools, and pipelines all rely on structured, reusable logic. Steady progress 🚀 #GenAI #PythonLearning #LLM #FineTuning #AgenticAI #LearningInPublic

Project:  Built and deployed an end-to-end Sentiment Analysis web application using modern ML and backend tools. Model: DistilBERT Dataset Source: Kaggle : 🔗 https://lnkd.in/g-4v3TUv TechStack: Python Hugging Face Transformers DistilBERT FastAPI uvicorn HTML, CSS, JavaScript Git & GitHub 🔗 GitHub Repository: https://lnkd.in/g9XymNHv #machinelearning #python #huggingface #sentimentanalysis #fastapi #uvicorn

LeetCode Progress | 258. Add Digits (Python) Today I solved “Add Digits” on LeetCode. Problem: Given an integer num, repeatedly add its digits until the result has only one digit, and return it. My approach: I used an iterative digit-sum process. -- Repeatedly extracted digits using modulo and division -- Summed the digits until the number became a single digit -- Returned the final value Optimal approach (O(1) without loops): This problem follows the mathematical concept of a Digital Root. The result can be found using: -- If num == 0, return 0 -- Otherwise, return 1 + (num - 1) % 9 This avoids iteration entirely and runs in constant time. What I learned: -- Some problems that look iterative have hidden mathematical patterns -- Recognizing number properties (like digital roots) can lead to O(1) solutions -- Always look for a formula when repeated digit operations are involved #leetcode #python #dsa #datastructures #algorithms #coding #programming #problemSolving #softwareengineering #computerscience #interviewprep #codinginterview #100daysofcode #pythonprogramming