You will get I will develop a scalable image classification AIsolution for your business
Project details
Turn your images into business insights with custom image classification
I help businesses and developers build high-accuracy image classification models tailored to their data using modern deep learning architectures like CNN and Vision Transformer (ViT).
This service includes:
✔️ Image data preprocessing & augmentation
✔️ Feature extraction & model training
✔️ CNN and/or ViT architectures
✔️ Performance evaluation (Accuracy, Precision, Recall, F1)
✔️ Clear results and report
You’ll receive:
• Clean and reproducible Python code
• Trained model weights
• Evaluation metrics and charts
• Explanation of how the model works
Business value:
• Automate visual tasks
• Improve product categorization
• Enhance quality inspection
• Save manual tagging effort
Share your image data and I’ll suggest the best architecture for you
I help businesses and developers build high-accuracy image classification models tailored to their data using modern deep learning architectures like CNN and Vision Transformer (ViT).
This service includes:
✔️ Image data preprocessing & augmentation
✔️ Feature extraction & model training
✔️ CNN and/or ViT architectures
✔️ Performance evaluation (Accuracy, Precision, Recall, F1)
✔️ Clear results and report
You’ll receive:
• Clean and reproducible Python code
• Trained model weights
• Evaluation metrics and charts
• Explanation of how the model works
Business value:
• Automate visual tasks
• Improve product categorization
• Enhance quality inspection
• Save manual tagging effort
Share your image data and I’ll suggest the best architecture for you
Machine Learning Tools
ChatGPT, Keras, MLflow, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$50
|
Standard
$120
|
Advanced
$230
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 1 | 2 | 3 |
Model Validation/Testing | - | ||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100 - $280Frequently asked questions
About Christian Junior
Machine Learning Engineer|Predictive Modeling & Data Analysis (Python)
Yaounde, Cameroon - 1:51 pm local time
Are you looking to turn your data into accurate predictions and actionable insights?
I am a Machine Learning Engineer specialized in predictive modeling and data-driven solutions. I help businesses:
✔️ Build classification and regression models
✔️ Predict customer churn and sales
✔️ Segment customers using clustering
✔️ Improve model accuracy and performance
✔️ Clean, analyze, and structure datasets
Recent Projects
- Telco Churn Prediction (Classification models, feature engineering, evaluation)
- Sales Forecasting using ML techniques
- Customer Segmentation with K-Means
- Deep learning experiments (CNN, RNN, NLP models)
Technical Stack
- Python (Pandas, NumPy, Scikit-learn, PyTorch)
- SQL (MySQL, PostgreSQL)
- Data visualization (Matplotlib, Seaborn, Power BI)
- Model evaluation & optimization
My Approach
- Clear understanding of business goals
- Structured data analysis
- Clean and reproducible code
- Clear interpretation of results
I focus on delivering practical, reliable, and well-documented solutions.
Let’s discuss your project.
Steps for completing your project
After purchasing the project, send requirements so Christian Junior can start the project.
Delivery time starts when Christian Junior receives requirements from you.
Christian Junior works on your project following the steps below.
Revisions may occur after the delivery date.
Image data preparation
Organization of the dataset (folders by class or CSV annotations). Image preprocessing (resizing, normalization). Data augmentation (rotation, zoom, flip, etc. with OpenCV or Albumentations).
CNN model design and training
Definition of CNN or Vision Transformer (VIT) architecture. Training with PyTorch or TensorFlow. Evaluation with reliable metrics: accuracy, F1-score, confusion matrix.