I will build machine learning, deep learning, and nlp models using python
Machine Learning Engineer
About this Gig
Are you looking for a reliable expert to turn your data into intelligent, working AI solutions?
I specialize in end-to-end machine learning, deep learning, and NLP projects from raw data to a deployed, production-ready model. Whether you're a startup, researcher, or business, I'll build you a clean, well-documented solution that actually works.
What I can build for you:
- Predictive ML models (regression, classification, clustering)
- Deep learning models using TensorFlow / PyTorch / Keras
- NLP pipelines: sentiment analysis, text classification, named entity recognition, summarization
- Computer vision: image classification, object detection, CNNs
- Data preprocessing, EDA, and feature engineering
- Model evaluation, optimization, and deployment (Flask / FastAPI / Streamlit)
Tools & Tech: Python, Scikit-learn, TensorFlow, PyTorch, Keras, HuggingFace Transformers, NLTK, spaCy, Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook, Google Colab, Flask, FastAPI
Feel free to message me before ordering - I'm happy to discuss your project first!
My Portfolio
Other Data Science & ML Services I Offer
FAQ
What information do I need to provide to get started?
Share your dataset (CSV, Excel, or database), describe the problem you want to solve (e.g., predict churn, classify text, detect objects), and mention any preferred tools or output format. The clearer your brief, the faster we start.
What if my dataset is messy or incomplete?
No problem — data cleaning and preprocessing are included in all packages. Just share what you have and I'll handle the rest.
Can you explain the model results to me in simple terms?
Absolutely. Every delivery includes a summary explaining what the model does, how accurate it is, and what the results mean — no technical jargon required.
Do you deploy the model so it can be used in a real application?
Deployment (as a REST API via Flask or FastAPI, or a Streamlit web app) is included in the Premium package. It can be added to Standard as an extra.

