Note: Pdf file is well formatted and easy to read.

• Jupyter Notebook Support
• Run pip install -r requirements.txt to install all the dependencies in your environment.

• Run jupyter notebook in your terminal to open the notebook in your browser.
• Open the Project2.ipynb file and run the cells in the notebook.

• Open the Project2.pdf file to see the results of the notebook.

The model will be saved in the model folder in the format of date and time of training.

Github: lurkingryuu

The folder Dataset2 contains 2 folders, the FNA named folder contains 2 more folders ( benign folder contains image datas for 1074 benign cases and malignant folder contains image datas for 650 malignant cases).

1. Preprocessing of given labelled image datas (inside ‘FNA’ files).

2. Train and validate your model (CNN) with those preprocessed images.

3. Estimate and plot training and validation loss and accuracy function.

4. Fit the unlabelled images from file ‘test’ to your model and predict malignant or benign.

1. The folder “test” inside folder “Dataset2” contains unlabelled 14 images. Predict benign or malignant for those cases. [Use a CNN (Convolutional Neural Network) OR any other deep neural network for training purpose].

2. Evaluate the model accuracy and loss function.