I will build custom machine learning and ai models in python tensorflow pytorch


About this gig
Looking for a reliable AI / Machine Learning developer who can actually ship?
I'm Pan an AI and Robotic Engineer who turns ML ideas into working, production-ready code. From a quick prototype to a full pipeline, I deliver clean Python, clear documentation, and results you can show your team or investors the same week.
WHAT I CAN BUILD FOR YOU
- Machine Learning models classification, regression, forecasting, clustering
- Deep Learning CNNs, RNNs, Transformers (TensorFlow, PyTorch, Keras)
- Computer Vision object detection, image classification, OCR, YOLO
- NLP & LLMs chatbots, sentiment analysis, text classification, OpenAI / Hugging Face APIs
- Data Science preprocessing, EDA, visualization, model evaluation
- AI integrations connect your model to a web app, API, or dashboard
MY STACK
Python TensorFlow PyTorch Keras Scikit-learn Pandas NumPy OpenCV Hugging Face FastAPI Streamlit
WHAT YOU GET IN EVERY ORDER
- Clean, commented source code (no spaghetti)
- Trained model file + evaluation metrics
- Short demo video walking you through the result
- Setup instructions and README
- Unlimited messaging during the project
Get to know Pan
AI and Robotic Engineer
- FromThailand
- Member sinceJul 2025
Languages
English
My Portfolio
Other AI Development Services I Offer
FAQ
I'm not sure which package I need. Can you help?
Absolutely — message me before ordering with a 2-3 sentence description of your project and I'll recommend the right package (or build a custom offer). Most clients pick Standard after we chat.
Do you provide the dataset, or do I?
You provide the data (CSV, images, text, etc.) and I handle everything from cleaning to modeling. If you don't have data, I can help you source a public dataset or scope a data collection plan.
What frameworks do you work with?
Python is my main language. I work daily with TensorFlow, PyTorch, Keras, Scikit-learn, Pandas, OpenCV, and Hugging Face. For deployment: FastAPI, Flask, Streamlit, Docker.
Will the code be commented and easy for my team to maintain?
Yes. Every line is documented and every project ships with a README explaining setup, training, and inference. Your team should be able to run it within minutes.
What if the model doesn't reach the accuracy I need?
I include revisions in every package to tune and improve performance. If we hit a ceiling that's a data limitation (not a modeling one), I'll tell you upfront and recommend next steps — no fluff.

