Contact person: Business Client

Phone:Show

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Location: London, United Kingdom

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Project Description:

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 + DenseNet example)
Assignment brief and marking criteria

Your job is to complete the full project to a high 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 (both models)
Example paper / similar study

Your Responsibilities:
Model Development

Train/validate/test both models
Tune hyperparameters
Solve issues (overfitting, imbalance, etc.)
Generate evaluation metrics:

Accuracy

Precision

Recall

F1 Score

AUC-ROC

Confusion Matrix
Produce graphs and tables

Written Report (~3000 words)

Must include:

Introduction

Literature Review

Methodology

Experiments & Results

Discussion

Conclusion

Appendix with code snippets & figures

Referencing: Harvard
Output: PDF + ZIP with scripts

Component 2 — Presentation (30%)

You will also prepare:

✔ 10-slide PowerPoint
✔ ~1000 words of speaker notes
✔ Harvard references

You may choose ONE topic from the list (CNNs, Image Processing, Multimodal AI, Ethics, etc.).

Required Skills:

TensorFlow or PyTorch

CNNs & transfer learning

Experience with DenseNet121

Medical imaging understanding (bonus)

Strong academic writing

Ability to generate clear visual results

Deliverables:

3000-word PDF report

Baseline CNN script (.py or .ipynb)

DenseNet121 script (.py or .ipynb)

Training logs, ROC curves, confusion matrix, graphs

PowerPoint slides (10 max)

Speaker notes (~1000 words)

Harvard reference list" (client-provided description)