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আপনার কার্ট
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Zinn Hub
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আপনার কার্ট
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AKORA

I build RAG-powered chatbots, web dashboards, and AI search systems for businesses | Python, OpenAI, Pinecone

📍 Located in: উগান্ডা 🕐
🎯🤝 এককালীন বা দীর্ঘমেয়াদী কাজের জন্য উন্মুক্ত 🌐 আপনার টাইমজোনে কাজ করতে পারে
👤 ফ্রিল্যান্সার
✔ যাচাইকৃত
⭐ জিনার লেভেল 1
🔗 AKORA অনলাইনে খুঁজুন
🔍

তারা কারা তা জানতে তাদের লিঙ্ক এবং এই প্রোফাইলের বাকি অংশগুলি দেখুন। Zinn Hub প্রতিটি Zinner-এর প্রোফাইল খোলা এবং স্বচ্ছ রাখে — যাতে আপনি বিশ্বাস তৈরি করতে পারেন এবং আত্মবিশ্বাসের সাথে নিয়োগ করতে পারেন।

💰 মূল্য নির্ধারণ
সাধারণ প্রতি ঘণ্টার হার: $12.00/ঘণ্টা
প্রকল্পগুলিতে আগ্রহী যার মূল্য: $12.00 – $15.00
🔒 আপনি সন্তুষ্ট না হওয়া পর্যন্ত Zinn Hub দ্বারা পেমেন্ট নিরাপদে রাখা হয় · কার্ড, পেপ্যাল, ক্রিপ্টো এবং আরও অনেক কিছু · কোনো ক্রেতা ফি নেই
✓

Zinn Hub দ্বারা যাচাইকৃত দক্ষতা

যাচাইকৃত Zinner

AKORA Zinn Hub-এ তাদের দক্ষতা প্রমাণ করেছে এবং তাদের কাজের প্রমাণ দিয়েছে। প্রতিটি যাচাইকৃত Zinner একটি হাতে-কলমে মান নিশ্চিতকরণ পর্যালোচনা পাস করে — যাতে আপনি আত্মবিশ্বাসের সাথে নিয়োগ করতে পারেন।

🛡️ October 2026 থেকে যাচাইকৃত

সদস্যপদ গ্রহণ
Oct 2026
তালিকাভুক্ত Zinns
0
শেষ সক্রিয়
19 hours আগে

সম্পর্কে

I am an AI Engineer who builds intelligent systems that help businesses unlock the value hidden inside their own data. My specialty is Retrieval-Augmented Generation (RAG) — the technology that transforms static documents, PDFs, and knowledge bases into interactive, AI-powered assistants that answer questions in plain English.

I discovered my passion for AI engineering through an intensive, hands-on scholarship program where I completed a comprehensive track covering the entire modern AI stack. Through this journey, I built multiple working systems from scratch — not just tutorials, but real, functional applications. I learned how to architect RAG pipelines, manage vector databases, engineer effective prompts, and deploy AI tools that solve actual problems.

আমি আপনার জন্য যা তৈরি করতে পারি:

RAG-Powered Chatbots: AI assistants that read your documents and answer customer or employee questions accurately, with citations to the original source.

Semantic Search Engines: Search tools that find information by meaning, not just keywords — so your team finds what they need even when they don't know the exact words.

Document Q&A Systems: Turn your PDFs, manuals, and knowledge bases into an instant-answer system that saves hours of manual searching.

Interactive AI Apps: User-friendly Streamlit applications that make your AI tools accessible to anyone, no technical skills required.

Data Processing Pipelines: Automated scripts that clean, batch, and prepare your data for AI systems using Pandas and NumPy.

My Technical Toolkit:

Python, Pandas, NumPy, OpenAI API (Embeddings, Chat Completions, Function Calling, Responses API), Pinecone, ChromaDB, LangChain, Streamlit, t-SNE, Matplotlib, Git, and REST API integration.

আমি কিভাবে কাজ করি:

I believe in clean, working solutions — not overcomplicated theory. I communicate clearly, deliver on time, and focus on understanding your actual problem before writing a single line of code. Whether you need a small prototype to test an idea or a complete system to automate a workflow, I will work with you to build something that genuinely helps.

I am early in my freelance journey, which means you get dedicated attention, competitive rates, and a genuine commitment to your project's success. I am not here to collect a paycheck — I am here to build a reputation, one happy client at a time.

If you have a document-heavy workflow, a customer support challenge, or an idea for an AI tool, let's talk. Send me a message and tell me what you're trying to solve. I will tell you honestly whether I can help — and if I can, I will give it everything I have.

দক্ষতা

এই ফ্রিল্যান্সার যে প্রযুক্তি এবং দক্ষতায় বিশেষজ্ঞ।

বিভাগসমূহ

এই ফ্রিল্যান্সার যে পরিষেবা ক্ষেত্রগুলির জন্য উপলব্ধ।

পোর্টফোলিও

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →

Semantic Search Engine for Clothing Reviews

Built a semantic search engine that finds similar customer reviews based on meaning, not just keywords. What it does: Processes thousands of e-commerce clothing reviews from a CSV dataset Generates embeddings using OpenAI's API and stores them in ChromaDB Applies t-SNE dimensionality reduction to visualize review clusters in 2D Implements a search function that returns the 3 most semantically similar reviews to any query Demonstrates real-world applications like automated feedback categorization (Quality, Fit, Style, Comfort) Tech Stack: Python, ChromaDB, OpenAI Embeddings, Pandas, NumPy, scikit-learn (t-SNE), Matplotlib

বিস্তারিত দেখুন →
📤 এই প্রোফাইল শেয়ার করুন
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Zinn Hub অ্যাপ পান

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