Easy Malaria Cell Classification with CNN and Python

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.

Code for this video: https://github.com/feitgemel/TensorFlowProjects/tree/master/Malaria%20Cell%20Classification

00:00 Intro !!!!!!!
00:25 Download and prepare the data
06:36 Build and train The CNN model
18:01 Test the model 

 ~~~~~~~~~~~~~~~ recommended courses and books ~~~~~~~~~~~~~~~
A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V 
I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ".
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