You will get I will build an NLP sentiment analysis or text classification API
Project details
I am a published AI/ML Engineer specializing in NLP systems
built with Python, BERT, and PyTorch. My research on
Transformer-based Speech Emotion Recognition achieved 83.2%
accuracy and was published in a peer-reviewed journal in 2025.
I build real NLP solutions — not just notebooks. From sentiment
analysis and text classification to named entity recognition
and custom BERT fine-tuning, I deliver clean, tested, and
documented pipelines that work in production.
What you get:
• Custom NLP model trained on your data
• Full pipeline: preprocessing → training → evaluation
• Source code + documentation in every tier
• FastAPI deployment available as add-on
Past NLP work includes:
• BERT Sentiment Analysis REST API
• Speech Emotion Recognition (Transformer-based, peer-reviewed)
• Multi-class text classification systems
Clear communication, on-time delivery, working code.
Message me and let's build your NLP solution today.
built with Python, BERT, and PyTorch. My research on
Transformer-based Speech Emotion Recognition achieved 83.2%
accuracy and was published in a peer-reviewed journal in 2025.
I build real NLP solutions — not just notebooks. From sentiment
analysis and text classification to named entity recognition
and custom BERT fine-tuning, I deliver clean, tested, and
documented pipelines that work in production.
What you get:
• Custom NLP model trained on your data
• Full pipeline: preprocessing → training → evaluation
• Source code + documentation in every tier
• FastAPI deployment available as add-on
Past NLP work includes:
• BERT Sentiment Analysis REST API
• Speech Emotion Recognition (Transformer-based, peer-reviewed)
• Multi-class text classification systems
Clear communication, on-time delivery, working code.
Message me and let's build your NLP solution today.
Machine Learning Tools
BERT, NLTK, NumPy, Open Neural Network Exchange, OpenCV, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlow, Tesseract OCR, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$30
|
Standard
$70
|
Advanced
$130
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 19 days |
Number of Revisions | 1 | 2 | 4 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 2 |
Number of Graphs/Charts | 2 | 4 | 4 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
About Didar
AI/ML Engineer | Data Analyst | NLP | Published Researcher
Rawalpindi, Pakistan - 3:41 pm local time
I build production-ready AI systems and data solutions — from NLP pipelines and ML models to full-stack applications and data analysis dashboards.
Recent work includes a BERT sentiment analysis API, a multi-disease health prediction platform (Diabetes, Parkinson's, Pneumonia), and a face recognition system with liveness detection.
Stack: Python, PyTorch, TensorFlow, FastAPI, Scikit-learn, Pandas, NumPy, SQL, Streamlit, Linux.
Clear communication, clean code, working systems. Message me to get started.
Steps for completing your project
After purchasing the project, send requirements so Didar can start the project.
Delivery time starts when Didar receives requirements from you.
Didar works on your project following the steps below.
Revisions may occur after the delivery date.
Understand Your NLP Task
Review your dataset, language, and goals. Clarify any requirements before starting.
Data Cleaning & Preprocessing
Tokenize, clean and prepare text data. Handle noise, stopwords and class imbalance.