Datascience:COVID-19 Pneumonia Classification(Deep learning)

Would you like to learn how to predict if someone has a coronavirus infection through the X-ray of their lungs?

Would you like to build a convolutional neural network model using deep learning to detect Covid-19?

If the answer to any of the above questions is "YES," then this course is for you.

Enroll Now in this course, learn how to detect coronavirus in a patient through the X-ray reports of their lungs. This is the 

You might be wondering if it is really possible to detect coronavirus in a patient through the X-ray reports of their lungs. 

YES, IT IS POSSIBLE THROUGH DEEP LEARNING AND CONVOLUTIONAL NEURAL NETWORKS.

As we know, the coronavirus affects the lungs of the victims and causes pneumonia, especially termed as COVID pneumonia. Through deep learning technologies and convolutional neural networks, we can analyze the X-ray reports of lungs to the pixel level. Without any PCR or RDT test, coronavirus can be detected if the virus has infected the lungs of the patients through Convolutional Neural Network with approximately 98 percent accuracy.

This is a hands-on data science guided project on Covid-19 pneumonia classification. No unnecessary lectures. As our students like to say:

"Short, sweet, and to the point course"

The same techniques can be used in:

• Skin cancer detection
• Normal pneumonia detection
• Brain defect analysis 
• Retinal Image Analysis

And any other diseases that use image-based reporting, like X-ray reports.

Enroll now, and you will receive a CERTIFICATE OF COMPLETION, and we encourage you to add this project to your resume. At a time when the entire world is troubled by Coronavirus, this project can catapult your career to another level.

So bring your laptop and start building, training, and testing the Data Science Covid 19 Convolutional Neural Network model right now.

We will be completing the following tasks:

• Task 1: Getting Introduced to Google Colab Environment & Importing Necessary Libraries

• Task 2: Importing, Cloning & Exploring Dataset

• Task: 3 Data visualization (Image Visualization)

• Task 4: Data augmentation & normalization

• Task 5: Building a Convolutional Neural Network Model

• Task 6: Compiling & Training CNN Model

• Task 7: Performance evaluation & testing the model & saving the model for future use

So, grab a coffee, turn on your laptop, ENROLL NOW, and start learning right now.