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I will build deep learning models using tensorflow and pytorch
AI ML Engineer LLMs RAG Pipelines Chatbots Python
AI/ML Engineer specializing in GenAI, LLMs, and RAG systems. I build production-ready AI apps using Python, TensorFlow, PyTorch, and LangChain.
Generative AI & LLMs: RAG pipelines, vector databases (...
About this Gig
Are you looking to turn your data into a working deep learning model? I build custom neural networks using TensorFlow, PyTorch, and Keras trained, tested, and ready to use.
I recently built a CNN-based image classifier achieving 92%+ accuracy on real benchmark data proof I deliver working models, not just promises.
What I offer:
1. Custom Deep Learning Models CNN, RNN, LSTM, GRU architectures tailored to your task: image classification, object detection, or pattern recognition.
2. Data Preprocessing I clean and prepare your dataset properly. Clean data is the foundation of any accurate model.
3. Model Training Using TensorFlow and PyTorch, I train your model with proper validation to avoid overfitting.
4. Hyperparameter Tuning I fine-tune your model for the best accuracy and efficiency.
5. Model Evaluation & Delivery You get a trained model, full accuracy report, and clean, documented source code.
Real project experience: CNN-based traffic sign recognizer, 92%+ accuracy, using transfer learning and data augmentation.
Message me before ordering if you're unsure which package fits your project I'll confirm your data and goal first.
Programming language:
Python
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SQL
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Java
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NoSQL
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MLflow
APIs:
Other
Tools:
Jupyter Notebook
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OpenCV
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OpenNN
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TensorFlow
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Excel
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MLflow
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Colab
Frameworks:
Scikit-learn
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DeepPy
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Keras
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PyTorch
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Panda
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TensorFlow
Other Data Science & ML Services I Offer
FAQ
What kind of dataset do I need?
Images for classification/detection tasks, or structured data for prediction tasks. The more labeled data you have, the better the results.
What's the difference between the packages?
Basic gives you a trained working model. Standard adds testing, tuning, and documentation. Premium includes deployment-ready code and API integration.
Can you work with a small dataset?
Yes — I can use techniques like data augmentation and transfer learning to get good results even with limited data.
What will I receive at the end?
A trained model, an accuracy/performance report, and clean, documented source code.
