$2.00
Link for the tutorial : https://youtu.be/WlPuW3GGpQo
Link for the full post : https://eranfeit.net/how-to-classify-malaria-cells-using-convolutional-neural-network/
This tutorial provides a step-by-step easy guide on how to implement and train a CNN model for Malaria cell classification using TensorFlow and Keras.
🔍 What You'll Learn 🔍:
* Data Preparation - In this part, you'll download the dataset and prepare the data for training. This involves tasks like preparing the data , splitting into training and testing sets, and data augmentation if necessary.
* CNN Model Building and Training - In part two, you'll focus on building a Convolutional Neural Network (CNN) model for the binary classification of malaria cells. This includes model customization, defining layers, and training the model using the prepared data.
* Model Testing and Prediction - The final part involves testing the trained model using a fresh image that it has never seen before. You'll load the saved model and use it to make predictions on this new image to determine whether it's infected or not.