2021 deep learning class using Google Colab

PDL medicine

Phenotype prediction using cancer-related data

Overview

This project focuses on predicting phenotypes based on cancer-related data. It leverages various data science and machine learning techniques to analyze genetic and clinical data, aiming to identify patterns and correlations that can predict specific cancer phenotypes.

Objective

The primary objective of this project is to develop a predictive model that can accurately determine cancer phenotypes from a given dataset. This involves:

• Data preprocessing and cleaning to prepare the dataset for analysis.
• Exploratory data analysis to understand the dataset's characteristics and underlying patterns.
• Feature selection and engineering to identify the most relevant features for the predictive model.
• Model development and training using suitable machine learning algorithms.
• Evaluation of the model's performance and fine-tuning to improve accuracy.

Data

You can utilizes cancer-related datasets, which may include genetic sequences, clinical data, patient demographics, and other relevant information. Due to privacy concerns these datasets are not disclosed publicly.

Technologies Used

• Python: The primary programming language used for data processing and model development.
• Jupyter Notebook: For interactive development and documentation of the code.
• Pandas & NumPy: For data manipulation and numerical computations.
• Scikit-learn: For machine learning model development, training, and evaluation.
• Matplotlib & Seaborn: For data visualization.

Installation and Usage

To use this project, follow these steps:

1. Clone the repository to your local machine, or use the .ipynb file directly in Google Colab.
2. Open the PDL_for_medicina.ipynb notebook in Jupyter to view the project's code and documentation.
3. Follow the instructions within the notebook to run the analysis and model training processes.

Contact

For any queries or further information, please contact the project maintainer via Issues. This file was made when I was beginning to work with DL and medicine, at about 2021, using Google Colab.