Lung Cancer Detection using Deep Learning

In this video, we are going to see how to predict Lung Disease Detection Using Deep Learning in Python. Machine learning is the study of algorithms that can improve automatically through experiences by using trained data. And while creating the Machine learning model with those data or models, it should be clean and classified in the proper ways. 

To predict lung cancer we will start with data importing and organizing the data: To get a better understanding of what does a dataset contains and how data is used to train our model. 

And then we will use the EDA of these datasets: Exploratory data analysis is the approach of analyzing the critical process of performing an initial investigation of the dataset to discover patterns and anomalies, and form hypotheses based on our understanding of the datasets. It is used to analyze data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. And then we will test the accuracy of our classifier after then build the model to predict the future outcome and then evaluate the trained model’s accuracy Code - 

https://www.kaggle.com/akshitmadan/lung-cancer-prediction/