Application of Python in the Healthcare Technology: Medical Data Analysis and Developing ML/AI Models
Autor Praveen Kumar Men Limba Engleză Paperback – dec 2025
Coverage defines how to set up an environment to work with python, describes Python class, methods, and functions, explains both basic and advanced statistical analysis in Python, and provides a tool to assist in the development of deep learning models such as API, Git, Github, NumPy, Pandas, and SciPy.
- Covers Python programming, from beginner level to advanced
- Uses the programming language Python to show doctors and other allied healthcare graduates how to impact patient care with world-class technology
- Follows the principle of utility-based learning rather than technical-based learning to suit the needs of medical graduate audience
- Covers hot topics like deep learning and advanced statistics
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Specificații
ISBN-13: 9780443219191
ISBN-10: 0443219192
Pagini: 180
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
ISBN-10: 0443219192
Pagini: 180
Dimensiuni: 191 x 235 mm
Editura: ELSEVIER SCIENCE
Cuprins
1. Requirements to be installed for setting up an environment to work with python
2. Built-in Data structures in python
3. Python Class, Methods and Functions
4. Analyzing data using Pandas and numpy
5. Basic statistical analysis in Python
6. Advanced statistical analysis in Python
7. Graphical visualization using matplotlib
8. Developing machine learning models using scikit-learn
9. Developing deep learning models using tensorflow
10. Developing image classifier and image identifier model using deep learning techniques
11. Accessing web using Active Programming Interface (API)
12. Version control system using Git and Github
13. Websites for staying abreast with the latest developments in python
2. Built-in Data structures in python
3. Python Class, Methods and Functions
4. Analyzing data using Pandas and numpy
5. Basic statistical analysis in Python
6. Advanced statistical analysis in Python
7. Graphical visualization using matplotlib
8. Developing machine learning models using scikit-learn
9. Developing deep learning models using tensorflow
10. Developing image classifier and image identifier model using deep learning techniques
11. Accessing web using Active Programming Interface (API)
12. Version control system using Git and Github
13. Websites for staying abreast with the latest developments in python