Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection

A practical hands on Deep Learning Project on building a Pneumonia Detection model using Tensorflow, CNN and OpenCV
3.91 (16 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection
85
students
2 hours
content
Oct 2024
last update
$44.99
regular price

Why take this course?

🎉 Data Science: CNN & OpenCV - Chest XRAY-Pneumonia Detection 🏥✨

Headline:
Dive into the world of AI and Machine Learning with our practical, hands-on project! Learn to build a high-accuracy Pneumonia Detection model using Tensorflow, Convolutional Neural Networks (CNN), and OpenCV on Chest XRays.


Course Overview:

If you're passionate about AI and its applications in healthcare, this is the course for you! We will guide you through the entire process of detecting Pneumonia from Chest XRays using Deep Learning models. This includes data exploration, augmentation, model training, evaluation, and deployment. By the end of this course, you'll have a solid understanding of how to implement a real-world AI project using Tensorflow and OpenCV.

Project Steps:

  1. Project Overview
  2. Introduction to Google Colab
  3. Understanding the Project Folder Structure
  4. Understanding the Dataset
    5-7. Setting Up the Project in Google Colab (Parts 1 & 2)
  5. Importing Libraries
  6. Plotting Data Counts
  7. Data Visualization Samples
  8. Creating a File Counter Method
  9. Calculating Class Weights
    13-15. Implementing Data Augmentation
    16-17. Understanding Model Checkpoints
    18-20. Model Fitting & Prediction
    21-23. Evaluating the Model with Classification Report, Confusion Matrix, and Plotting Accuracy/Loss
    24-26. Saving and Loading the Trained Model
  10. Real-World Application: Predicting Pneumonia from an Image

Course Highlights:

  • Comprehensive Pipeline Coverage: From data loading to prediction, you'll learn it all!
  • Essential Skills for Healthcare Diagnostics: Perfect your skills in detecting Pneumonia, especially relevant in the context of COVID-19.
  • Hands-On Learning Experience: Work with real datasets and develop a project from scratch.
  • Educational Resources Included: Receive a Jupyter notebook and other project files upon course completion.
  • Certificate of Completion: Showcase your new skills with a certificate from AutomationGig.

Why Enroll Now?

Machine Learning is revolutionizing the healthcare industry, and this course will equip you with the knowledge to contribute to this field. By mastering Tensorflow, CNNs, and OpenCV, you'll be ready to tackle complex problems and make an impact. Plus, it's an in-demand skill set for the 21st century!


What You'll Receive:

  1. Certificate of Completion
  2. Jupyter Notebook & Project Files

Get Started Today!

With a cup of coffee and a few hours, you can embark on a journey to become proficient in one of the most sought-after skills today. Click "ENROLL NOW" and join us inside the course for an unforgettable learning experience!
🎉 Happy Learning! 📚


Important Note:

This course is intended for educational purposes only. We encourage responsible use of AI and ML technologies to benefit humanity. Let's learn, innovate, and improve lives together!
[Music by bensound]


Enroll now and take the first step towards becoming a master in Data Science with CNN & OpenCV for Chest XRAY-Pneumonia Detection! 🚀

Course Gallery

Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection – Screenshot 1
Screenshot 1Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection
Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection – Screenshot 2
Screenshot 2Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection
Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection – Screenshot 3
Screenshot 3Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection
Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection – Screenshot 4
Screenshot 4Data Science: CNN & OpenCV : Chest XRAY-Pneumonia Detection

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4529706
udemy ID
02/02/2022
course created date
08/05/2022
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