Potato Disease

Table of Contents:

1. Description

2. Dataset

3. Data Preprocessing

4. Building the Model

5. Evaluation

1. Description

I build a machine learning model using tensorflow that can detect if there are early blight and late blight diseases in potato plant. The goal of this project to accurately identify those disease so that farmers can take step.

2. Dataset

The datset is collected from kaggle.

3. Data Preprocessing

1. Data analysis
2. Split the dataset
   • I split the dataset with 80% of training set and 20% of test set.

4. Building the Model

1. Creating a Layer for resizing and normalization.
2. Data Augmentation
3. Model Architecture
   • Conv2D for CNN
   • MaxPooling2D for pooling
   • relu & softmax for activation function
   • adam for optimization

5. Evaluation

* `accuracy`