![Breast cancer Diagnostics Full Modeling [Ref: TT10040]](/store/1/imgTemp/pink-ribbon-feature.jpg)
Breast cancer Diagnostics Full Modeling [Ref: TT10040]
in ML FoundationsAbout this course
ENROLLING COHORT 4 NOW!!
Build your skills in the application of machine learning in healthcare and medical diagnostics. This project will build your mastery of the key stages of analytics and predictive modeling in healthcare as you work with our project team to design, develop and implement a breast cancer diagnostic system
Problem Statement :
The application of machine learning approaches to medical diagnostics has grown explosively in recent years. The breast cancer diagnostics project enables participants to build intermediate-level skills in the application of data science and machine learning-based approaches to improving the quality and speed of medical diagnostics in patient care across the healthcare delivery spectrum
Aim :
This project aims to create mastery in candidates to build a model able to predict the diagnosis of breast cancer tissues as malignant or benign. Participants will learn how to combine biology, chemistry, physics, and data science to uncover insights or find previously hidden patterns which in this case will be to predict whether a cancer cell is malignant or benign
Data for this project is drawn from digitized images of a fine needle aspirate (FNA) of a breast mass that describe characteristics of the cell nuclei present in the image
What you will learn :
- Data Analytics toolset for health/medical diagnostics
- Data Cleaning and Feature Engineering
- Multiple Modeling Approaches for Medical data features
- Model Performance Tunning
- API-based model serving
This project features JIT-based training in Python and as such, candidates are not required to possess any skills in Python
