You will get NLP & LLM Fine-Tuning for Text Analysis
Project details
I help businesses extract actionable insights from text data using NLP and Large Language Models. From sentiment analysis to text summarization and custom LLM fine-tuning, I build pipelines that improve customer engagement and automate knowledge-driven processes. My solutions are scalable, accurate, and optimized for efficiency.
Deliverables include:
--> Text preprocessing & NLP pipeline
--> LLM fine-tuning for custom tasks
--> Domain-specific model customization
--> Integration with APIs/Chatbots
--> Deployment & documentation
Deliverables include:
--> Text preprocessing & NLP pipeline
--> LLM fine-tuning for custom tasks
--> Domain-specific model customization
--> Integration with APIs/Chatbots
--> Deployment & documentation
AI Algorithms
Convolutional Neural Network, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Multimodal Large Language Model, Recurrent Neural Network, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Content Creation, Conversational AI, Natural Language Generation, Natural Language Understanding, Sentiment Analysis, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$300
|
Standard
$850
|
Advanced
$1,700
|
|---|---|---|---|
| Delivery Time | 6 days | 12 days | 22 days |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code | - | - | - |
About Huzaifa
Full Stack Web Developer | MERN Stack | React, Next.js, Node, Nest.js
Gujrat, Pakistan - 7:52 am local time
Whether you need a SaaS platform, dashboard, or enterprise-grade API, I ensure every project delivers fast performance, clean structure, and seamless user experiences, optimized for both functionality and growth.
💼 𝑺𝒆𝒓𝒗𝒊𝒄𝒆𝒔
✔️ Custom full-stack web application development
✔️ Front-end development with React & Next.js
✔️ Backend architecture using Node.js & Nest.js
✔️ API design (REST & GraphQL)
✔️ Secure authentication and authorization systems
✔️ Database modeling (MongoDB, PostgreSQL)
✔️ Integration with third-party APIs (Stripe, AWS, etc.)
✔️ Deployment, scaling, and maintenance support
✨ 𝑺𝒌𝒊𝒍𝒍𝒔 & 𝑬𝒙𝒑𝒆𝒓𝒕𝒊𝒔𝒆
✔️ React.js, Next.js, Node.js, Nest.js
✔️ Flutter, Dart
✔️ Express.js, TypeScript
✔️ MongoDB, PostgreSQL, MySQL
✔️ REST APIs, GraphQL
✔️ JWT, OAuth2, Firebase Auth
✔️ TailwindCSS, Material UI, Chakra UI
✔️ Docker, Nginx, CI/CD pipelines
🛠 𝑻𝒐𝒐𝒍𝒔 & 𝑻𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒊𝒆𝒔
✔️ VS Code, Postman, GitHub, Bitbucket
✔️ Docker, AWS, GCP, Vercel, Heroku
✔️ Stripe, PayPal, Twilio, SendGrid integrations
✔️ Trello, Slack, Jira
✨ 𝑾𝒉𝒚 𝑾𝒐𝒓𝒌 𝑾𝒊𝒕𝒉 𝑴𝒆
✔️ Proven expertise in building scalable custom web solutions
✔️ Strong command over modern frameworks (Next.js, Nest.js)
✔️ Focus on clean architecture and modular code
✔️ High responsiveness and clear communication
✔️ Post-launch support and code maintenance
🚀 𝑳𝒆𝒕’𝒔 𝑩𝒖𝒊𝒍𝒅 𝒀𝒐𝒖𝒓 𝑵𝒆𝒙𝒕 𝑾𝒆𝒃 𝑨𝒑𝒑!
Message me, and I’ll help create a scalable, high-performing solution for your business.
Steps for completing your project
After purchasing the project, send requirements so Huzaifa can start the project.
Delivery time starts when Huzaifa receives requirements from you.
Huzaifa works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
Review your data, domain, and objectives to define the NLP or LLM fine-tuning strategy and success metrics.
Data Cleaning & Preprocessing
Prepare text using NLP techniques such as normalization, tokenization, and noise removal to ensure high-quality inputs.