I will build image classification and machine learning models in python
About this Gig
Are you looking for an accurate image classification, computer vision, or machine learning solution developed in Python?
I will build, train, evaluate, and improve machine learning or deep learning models according to your dataset and project requirements. I have practical experience working with image classification, object detection, fire and smoke detection, vehicle recognition, data preprocessing, model evaluation, and AI application development.
My services include:
Image and multi-class classification
Computer vision and object detection
Machine learning model development
CNN and transfer learning models
Data cleaning and preprocessing
Exploratory data analysis and visualization
Feature engineering and model selection
Hyperparameter tuning
Accuracy, precision, recall, F1-score, and confusion matrix
Python scripts and Jupyter Notebook
Flask or FastAPI model integration
Well-commented source code and documentation
Technologies:
Python, TensorFlow, Keras, PyTorch, Scikit-learn, OpenCV, Pandas, NumPy, Matplotlib and YOLO.
Every project has different requirements. Please message me with your dataset and expected output before placing an order.
Programming language:
Python
•
MATLAB
Frameworks:
Scikit-learn
•
DeepPy
•
Keras
•
PyTorch
•
Panda
Tools:
Jupyter Notebook
•
OpenCV
•
OpenNN
•
TensorFlow
•
Colab
My Portfolio
FAQ
Do you develop image classification models?
Yes. I can develop binary, multi-class, and multi-label image classification models using CNNs, transfer learning, TensorFlow, Keras, or PyTorch.
Can you work with my own dataset?
Yes. Please share the dataset format, size, classes, and expected results before ordering.
Will you provide source code?
Yes. You will receive properly organized and commented Python code or a Jupyter Notebook.
Can you improve an existing model?
Yes. I can analyze your model, fix preprocessing issues, tune parameters, improve evaluation, and reduce overfitting where possible.
Will you guarantee a particular accuracy?
No fixed accuracy can be guaranteed before inspecting the dataset. Final performance depends on data quality, quantity, class balance, labeling, and task complexity.

