https://github.com/professorlearncode/professorlearncode
Config files for my GitHub profile.
https://github.com/professorlearncode/professorlearncode
config github-config
Last synced: 5 months ago
JSON representation
Config files for my GitHub profile.
- Host: GitHub
- URL: https://github.com/professorlearncode/professorlearncode
- Owner: ProfessorlearnCode
- Created: 2023-09-04T11:45:02.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-06-09T15:40:12.000Z (about 1 year ago)
- Last Synced: 2025-06-09T16:38:07.060Z (about 1 year ago)
- Topics: config, github-config
- Homepage: https://github.com/ProfessorlearnCode
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## 💫 About Me:
Hey there 👋🏻
I’m Farzam — I like building things that blend software, hardware, and a sprinkle of AI.
Whether it’s cooking with code, setting up IoT systems, or exploring the cloud, I’m all about taking ideas from “_what if 🤔?_” to “_check this out 👀!_”
---
### 🔭 What I'm Building
_A few cool things I’m working on — and probably still proud of even a year from now!_
- ☁️ **_Setting up and exploring GCP + OCI_**: Learning how to deploy apps, manage virtual machines, configure storage, and understand cloud-native architecture. I’m treating this as a foundation for future scalable deployments, CI/CD pipelines, and understanding real-world DevOps workflows. GCP’s AI tooling and Oracle’s free-tier infra are making experimentation pretty accessible.
- 🍲 **Intelligent Nutri — _an AI-powered cooking assistant_**: A full-stack web app that recommends recipes based on user preferences, offers AI chat cooking guidance, and integrates nutrition data — built with HTML/CSS/JS, Flask, FAISS (for semantic search), and Gemini API.
- 📸 **PixId — _Smart Attendance System with ESP32-CAM + Flask_**: Using ESP32-CAM and Flask to create an offline-capable attendance system that captures motion-triggered images over a local Wi-Fi AP. Practical for IoT learning, edge processing, and embedded automation.
---
### 🌱 What I’m Exploring Right Now
_There’s always something new everyday, and so here's what I am looking out for..._
- ⚙️ **_Backend Development with Flask_**: Building **REST APIs**, handling database logic, and connecting it all with frontend frameworks. I'm using Flask in most of my current projects — from AI chatbots to IoT servers. It’s clean, simple, and very Pythonic, which makes it my go-to for quick iterations and solid backend foundations.
- 🧱 **_System Design & Diagrams_**: I’ve been focusing on understanding how to architect scalable systems — thinking in terms of components, databases, APIs, caching, queues, and failure points. I'm also practicing how to document everything visually using tools like draw\.io or Mermaid.js for clarity and collaboration.
- 🛠️ **_Git & GitHub Code Spaces_**: Git is basically my second keyboard shortcut at this point. I'm using it not just for version control, but also for team collaboration, issue tracking, and managing feature branches. Recently, I’ve started exploring **GitHub Codespaces** to code from anywhere without worrying about local setup — and it's a game changer for portable development.
- 🤖 **_Embedded Systems_**, IoT & Microcontrollers: Working hands-on with **ESP32-CAM**, sensors, and basic breadboard circuits. I’m building systems where devices detect motion, capture images, and send them over WiFi to a local server. It’s low-level but super satisfying — like giving life to circuits with logic.
- ☁️ **_Cloud & DevOps (GCP + OCI)_**: I’ve been exploring "Google Cloud Platform" and **Oracle Cloud Infrastructure** — deploying apps, managing VMs, and understanding cost optimization and high availability. This is helping me bridge the gap between writing code and making sure it runs reliably in the real world.
- 🧠 **_AI Logic & Model Implementation_**: Beyond calling APIs, I’m trying to **understand what’s under the hood** — how LLMs process input, how vector stores like **FAISS** handle semantic search, and how to structure pipelines for AI-powered features. This includes working with tools like OpenAI and Gemini to build conversational interfaces and intelligent recommendation systems.
- 🎯 **_Prompt Design & Fine-Tuning_**: It’s not just about sending a prompt and getting a response — I’m learning how to **craft prompts with intent**, how context affects AI output, and even exploring lightweight fine-tuning methods or embeddings to improve personalization. This comes into play a lot with projects like my *Intelligent Nutri* assistant.
---
### 💬 Let’s Talk About
_Introverted but enthusiatic, all up for tech talks..._
- Frontend magic + GSAP – Animations, interactive UIs, and building smooth user experiences. If you want to make things move and feel right, I’m into it.
- Flask & full-stack workflows – How to connect frontend to backend, build REST APIs, and manage databases — especially for AI-integrated apps.
- LLMs & prompt engineering – Whether it’s plugging in OpenAI or Gemini APIs, crafting better prompts, or using FAISS for semantic search — I enjoy making AI actually useful in real-world apps.
- IoT + ESP32 projects – From camera modules to motion sensors, I can walk you through setting up microcontrollers, capturing data, and sending it to a local server — no internet needed.
- Cloud basics with GCP & OCI – Just getting started here, but if you're figuring out deployment, infra, or testing the cloud waters like me, let's swap notes.
- Project brainstorming + system design – I like breaking big ideas into clear, doable pieces and designing systems that actually work — whiteboards, diagrams, and all.
---
### ⚡ Fun fact
Half my project ideas start as anime references and end up on GitHub 😄
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## 🌐 Socials: [](https://instagram.com/thesilentmaestro) [](https://linkedin.com/in/in/farzam-asad-387340288) [](mailto:farzam.professor@gmail.com)
## 💻 Tech Stack:
                                   
## 📊 GitHub Stats:
## ✍️ Random Dev Quote
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[](https://visitcount.itsvg.in)