Learn 3D Image Classification With Python And Keras

Learn to predict viral pneumonia in CT scans with the help of 3D CNNs in Python and Keras : Hands-on

What you'll learn

Understanding of 3D image classification and its applications in medical imaging, specifically in classifying viral pneumonia in CT scans.

Knowledge of how to use Python, Keras, and TensorFlow to build a 3D convolutional neural network (CNN) for image classification.

Hands-on experience in pre-processing and preparing 3D images for input into a machine learning model.

Understanding of the architecture and parameters used in a 3D convolutional neural network.

Requirements

Basic knowledge of Python Programming

Description

Welcome to the "Learn 3D Image Classification with Python and Keras" course. In this comprehensive and hands-on course, you will learn how to build a powerful 3D convolutional neural network (CNN) for classifying CT scans. With the use of the Google Colab platform, Python, and Keras in TensorFlow, you will be able to effectively analyse medical images and predict the presence of viral pneumonia in computer tomography (CT) scans.Medical imaging plays a vital role in disease diagnosis, and this course will provide you with the necessary skills and techniques to excel in this field. You will be able to tackle real-world challenges and gain a strong foundation in 3D image classification and deep learning. This is an excellent opportunity for healthcare professionals, data scientists, and anyone looking to advance their AI skills.By the end of this course, you will have a complete understanding of how to classify 3D images using Python and Keras. You will have a portfolio project that you can showcase to potential employers and be able to confidently apply your skills in a professional setting. With its clear and concise approach, this course is designed to maximize your learning potential in the shortest time possible.Enroll now and take the first step towards a fulfilling career in 3D image classification and AI. Happy Learning!

Overview

Section 1: Fundamentals

Lecture 1 Introduction

Lecture 2 What is Computer Vision?

Lecture 3 What is 3D Image Classification ?

Lecture 4 Our Project

Lecture 5 How 3D Image Classification is done?

Lecture 6 Why Python and Keras?

Lecture 7 Why Google Colab?

Section 2: Model Building and Prediction

Lecture 8 Create a “3d_classification” folder

Lecture 9 Upload Dataset

Lecture 10 Python Code

Lecture 11 Pre-Trained Model

Lecture 12 Prediction Folder

Lecture 13 Enabling GPU in Google Colab

Lecture 14 Is GPU connected to Colab notebook?

Lecture 15 Connect Google Colab with Google Drive

Lecture 16 Import Libraries

Lecture 17 Specify Directory

Lecture 18 Check the number of CT scans

Lecture 19 Visualize a Sample CT Scan

Lecture 20 Preprocessing

Lecture 21 Create Labels for the CT Scans

Lecture 22 Splitting Data

Lecture 23 Data Pre-Processing and Augmentation

Lecture 24 Visualizing an Augmented CT Scan

Lecture 25 Model Building

Lecture 26 Visual Representation of 3D CNN

Lecture 27 Model Compilation

Lecture 28 Callbacks

Lecture 29 Training

Lecture 30 Loading Pre-Trained Weights

Lecture 31 Prediction

Anyone who is interested in learning about 3D image classification and building a 3D convolutional neural network using Python, Keras, and TensorFlow on the Google Colab platform.,AI enthusiasts who are eager to learn how to develop a deep learning model from scratch and want to apply their knowledge to the medical imaging domain.,Data scientists and machine learning engineers who are interested in expanding their skill set in the field of medical imaging analysis and want to work on real-world projects.,Healthcare professionals, such as radiologists and medical technicians, who are interested in utilizing advanced AI techniques to improve the accuracy of disease diagnosis from medical imaging data.