Full Academic Deep Learning / Machine Learning Project – Cardiomegaly Detection
Budget: $10 – $30 USD
I am looking for an experienced Deep Learning / Machine Learning professional to complete a full academic-style project.
I will provide:
Dataset (train, validation, test images)
Example baseline code (starter CNN + DenseNet121 example)
Assignment brief and marking criteria
Your job is to complete the full project to a high academic standard.
Component 1 — Coursework (70%)
Task
Build and compare two models for Cardiomegaly detection in chest X-ray images:
Baseline CNN (custom architecture)
DenseNet121 (transfer learning)
What I Will Give You
Full dataset (224×224 images)
Starter code for both models
Example paper / similar study
Your Responsibilities
Model Development
Train/validate/test both models
Tune hyperparameters
Address issues such as:
Overfitting
Class imbalance
Generate evaluation metrics:
Accuracy
Precision
Recall
F1 Score
AUC-ROC
Confusion Matrix
Produce clear graphs and tables to present results
Written Report (~3000 words)
The report must include:
Introduction
Literature Review
Methodology
Experiments & Results
Discussion
Conclusion
Appendix with code snippets & figures
Referencing style: Harvard
Output
PDF report
ZIP file with all scripts and relevant files
Component 2 — Presentation (30%)
You will also prepare:
✔ PowerPoint presentation (max 10 slides)
✔ ~1000 words of speaker notes
✔ Harvard reference list
You may choose one topic from a list (e.g., CNNs, Image Processing, Multimodal AI, Ethics in AI, etc.).
Required Skills
TensorFlow or PyTorch
CNNs & transfer learning
Experience with DenseNet121
(Bonus) Medical imaging understanding
Strong academic writing skills
Ability to generate clear visual results (graphs, plots, tables)
Deliverables
3000-word PDF report
Baseline CNN script (.py or .ipynb)
DenseNet121 script (.py or .ipynb)
Training logs, ROC curves, confusion matrix, and other graphs
PowerPoint slides (up to 10)
Speaker notes (~1000 words)
Full Harvard reference list
Important – Pricing & Policy
Your bid must reflect your final price for completing all deliverables listed above.
Requests to increase the price after the project is awarded will not be accepted.
If you attempt to charge more than your original bid or pressure for extra payment beyond what is agreed on the platform, this will be reported to Freelancer as a violation of platform rules.
Only bid if you fully understand the scope and are confident you can deliver everything at the price you submit.
I will provide:
Dataset (train, validation, test images)
Example baseline code (starter CNN + DenseNet121 example)
Assignment brief and marking criteria
Your job is to complete the full project to a high academic standard.
Component 1 — Coursework (70%)
Task
Build and compare two models for Cardiomegaly detection in chest X-ray images:
Baseline CNN (custom architecture)
DenseNet121 (transfer learning)
What I Will Give You
Full dataset (224×224 images)
Starter code for both models
Example paper / similar study
Your Responsibilities
Model Development
Train/validate/test both models
Tune hyperparameters
Address issues such as:
Overfitting
Class imbalance
Generate evaluation metrics:
Accuracy
Precision
Recall
F1 Score
AUC-ROC
Confusion Matrix
Produce clear graphs and tables to present results
Written Report (~3000 words)
The report must include:
Introduction
Literature Review
Methodology
Experiments & Results
Discussion
Conclusion
Appendix with code snippets & figures
Referencing style: Harvard
Output
PDF report
ZIP file with all scripts and relevant files
Component 2 — Presentation (30%)
You will also prepare:
✔ PowerPoint presentation (max 10 slides)
✔ ~1000 words of speaker notes
✔ Harvard reference list
You may choose one topic from a list (e.g., CNNs, Image Processing, Multimodal AI, Ethics in AI, etc.).
Required Skills
TensorFlow or PyTorch
CNNs & transfer learning
Experience with DenseNet121
(Bonus) Medical imaging understanding
Strong academic writing skills
Ability to generate clear visual results (graphs, plots, tables)
Deliverables
3000-word PDF report
Baseline CNN script (.py or .ipynb)
DenseNet121 script (.py or .ipynb)
Training logs, ROC curves, confusion matrix, and other graphs
PowerPoint slides (up to 10)
Speaker notes (~1000 words)
Full Harvard reference list
Important – Pricing & Policy
Your bid must reflect your final price for completing all deliverables listed above.
Requests to increase the price after the project is awarded will not be accepted.
If you attempt to charge more than your original bid or pressure for extra payment beyond what is agreed on the platform, this will be reported to Freelancer as a violation of platform rules.
Only bid if you fully understand the scope and are confident you can deliver everything at the price you submit.