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તમારી કાર્ટ
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Zinn Hub
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તમારી કાર્ટ
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AKORA

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

📍 Located in: યુગાન્ડા 🕐
🎯🤝 એક-વખતના અથવા લાંબા ગાળાના કામ માટે ખુલ્લું 🌐 તમારા સમય ઝોનમાં કામ કરી શકે છે
👤 ફ્રીલાન્સર
✔ ચકાસાયેલ
⭐ Zinner લેવલ 1
🔗 AKORA ઑનલાઇન શોધો
🔍

તેઓ કોણ છે તે જાણવા માટે તેમની લિંક્સ અને આ પ્રોફાઇલના બાકીના ભાગનું અન્વેષણ કરો. Zinn Hub દરેક Zinnerની પ્રોફાઇલને ખુલ્લી અને પારદર્શક રાખે છે — જેથી તમે વિશ્વાસ બનાવી શકો અને આત્મવિશ્વાસ સાથે હાયર કરી શકો.

💰 કિંમત
સામાન્ય કલાકદીઠ દર: $12.00/કલાક
મૂલ્યવાન પ્રોજેક્ટ્સમાં રસ છે: $12.00 – $15.00
🔒 તમે સંતુષ્ટ ન થાઓ ત્યાં સુધી Zinn Hub દ્વારા ચુકવણીઓ સુરક્ષિત રીતે રાખવામાં આવે છે · કાર્ડ્સ, PayPal, ક્રિપ્ટો અને વધુ · કોઈ ખરીદનાર ફી નથી
✓

Zinn Hub દ્વારા ચકાસાયેલ કૌશલ્યો

ચકાસાયેલ ઝિનર

AKORA એ Zinn Hub ને તેમની કૌશલ્ય સાબિત કરી છે અને તેમના કાર્યના પુરાવા પૂરા પાડ્યા છે. દરેક વેરિફાઇડ Zinner હાથથી ગુણવત્તા ખાતરી સમીક્ષા પાસ કરે છે — જેથી તમે વિશ્વાસ સાથે નોકરી પર રાખી શકો.

🛡️ October 2026 થી ચકાસાયેલ

ના સભ્ય
Oct 2026
સૂચિબદ્ધ ઝિન્સ
0
છેલ્લી સક્રિય
18 hours પહેલાં

વિશે

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.

હું તમારા માટે શું બનાવી શકું છું:

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.

હું કેવી રીતે કામ કરું છું:

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.

કુશળતા

આ ફ્રીલાન્સર જે ટેકનોલોજી અને કુશળતામાં નિષ્ણાત છે.

શ્રેણીઓ

આ ફ્રીલાન્સર માટે ઉપલબ્ધ સેવા ક્ષેત્રો.

પોર્ટફોલિયો

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

વિગતો જુઓ →

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

વિગતો જુઓ →

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

વિગતો જુઓ →

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

વિગતો જુઓ →

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

વિગતો જુઓ →

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

વિગતો જુઓ →

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

વિગતો જુઓ →
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