You will get a custom NLP text classification pipeline with clean code and frontend.
Project details
You will get a production-ready NLP text classification
pipeline built on your real-world text data.
Proven results: ~90% classification accuracy achieved
in real world projects with customer data using TF-IDF and tuned ML classifiers.
What you get:
• Text preprocessing (tokenization, stopword removal,
lemmatization, TF-IDF feature extraction)
• Multiple classifier benchmarking & selection
• Class imbalance handling
• Analytics of data with insights full charts
• Data Analytics — class distribution, word frequency,
text length analysis with charts
• WordCloud, confusion matrix & correlation heatmaps
• Full evaluation (accuracy, F1, precision, recall)
• Optional Streamlit dashboard & FastAPI endpoint
• Clean, documented Python code
Ideal for: sentiment analysis, spam detection, customer
feedback classification, or any text labeling problem.
pipeline built on your real-world text data.
Proven results: ~90% classification accuracy achieved
in real world projects with customer data using TF-IDF and tuned ML classifiers.
What you get:
• Text preprocessing (tokenization, stopword removal,
lemmatization, TF-IDF feature extraction)
• Multiple classifier benchmarking & selection
• Class imbalance handling
• Analytics of data with insights full charts
• Data Analytics — class distribution, word frequency,
text length analysis with charts
• WordCloud, confusion matrix & correlation heatmaps
• Full evaluation (accuracy, F1, precision, recall)
• Optional Streamlit dashboard & FastAPI endpoint
• Clean, documented Python code
Ideal for: sentiment analysis, spam detection, customer
feedback classification, or any text labeling problem.
Machine Learning Tools
Azure Machine Learning, ChatGPT, NLTK, NumPy, pandas, Python, Python Scikit-Learn, XGBoostWhat's included
| Service Tiers |
Starter
$20
|
Standard
$35
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 2 | 3 | 4 |
Number of Scenarios | 0 | 2 | 2 |
Number of Graphs/Charts | 5 | 8 | 10 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Muhammad
AI & Machine Learning | Artificial Intelligence, Data Scientist
Lahore, Pakistan - 5:40 pm local time
Machine Learning pipelines, Applied Data Science, and
Agentic AI systems.
I build production-ready ML models that solve real business
problems — not just notebooks. My work includes a churn
predictor (F1=0.62, Recall=0.70), a smartphone price
prediction API (R²=0.903), and a real-time Agentic AI
chatbot deployed on Hugging Face — all with live demos.
What I can do for you:
- End-to-end ML pipelines (data → deployed API)
- EDA, feature engineering & predictive modeling
- NLP pipelines & text classification
- Agentic AI chatbots using LangChain & LangGraph
- FastAPI + Streamlit dashboards
Final-year AI Engineering student at COMSATS Lahore with
hands-on NLP internship experience and 10+ deployed projects.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Text Analytics & EDA
Class distribution, word frequency, text length charts, WordCloud — understand your data before modeling.
Text Preprocessing & Cleaning
Tokenization, stopword removal, lemmatization and TF-IDF to transform raw text into structured features.