'Work on Predictive Analysis – Build an AI Powered Breast Cancer Detection Engine' | 60 min Bootcamp for Dr. Mahalingam College of Engineering and Technology

LEARNING OBJECTIVES

After completing this course you will:

  • Have a good working knowledge of the Fundamentals of Predictive Analysis.
  • Learn various concepts involved in building the Breast Cancer Prediction Engine such as Exploratory Data Analysis, and Support Vector Classification.
  • Have a fully functional prototype that you can customize, showcase, share, using the existing source code.
  • Be able to train the model on your custom dataset and fine tune the model to enhance its performance.

Complete this course in 3 easy steps to earn your certificate & badge!

STEP 1 : Watch the below self-guided tutorial.
STEP 2 : Practice as you watch the video by installing and working with the kandi 1-click solution kit.
STEP 3 : Complete the assessment to receive your certificate & badge.


STEP 1 : TUTORIAL

Watch this self-guided tutorial on how you can use Dataset to train the model, Exploratory Data Analysis, and Vector Classification to build your own AI Powered Breast Cancer Detection Engine.


STEP 2 : PRACTICAL EXERCISE

Click the below button to access the breast cancer detector kandi kit. This kit has all the required dependencies and resources you need to build your application.

Click on the 1-Click Installer button on the kandi kit page to install the breast cancer detector kit. On installing and running this kit, you will have a working model that you can customize and use in your project.

In case you want to review the session, feel free to watch the recording HERE.

kandi 1-Click Kit - Dark

Code Snippet Exercises

Below is a sample coding exercise that will help you advance in your journey in AI Breast Cancer Predictor. To get started, use the relevant keywords to search for simple code snippets in the search bar on kandi .

Sample Exercise 1 - Train test split python : Train test split is a model validation procedure that allows you to simulate how a model would perform on new/unseen data. Empirical studies show that the best results are obtained if we use 20-30% of the data for testing, and the remaining 70-80% of the data for training.


STEP 3 : ASSESSMENT

Complete a short assessment and earn your certificate & badge now. Congrats
Take Assessment

Your assessment will be reviewed and you will receive a verified certificate & badge via email within a week.


SUPPORT

Reach out to us by replying below for any help you may need with this course.

We hope you enjoyed using kandi! Continue your learning journey with kandi Congrats