In this video, I showcase my data science internship project with The Sparks Foundation, focusing on classifying iris flowers using the decision tree algorithm.
I utilized Python libraries like NumPy, Pandas, Matplotlib, and Seaborn for data manipulation, visualization, and analysis. Through exploratory data analysis with scatter plots, heatmaps, and pair plots, I explored relationships between attributes and the target variable.
I implemented and fine-tuned a decision tree model to classify iris flowers based on sepal and petal dimensions. A highlight is the graphical visualization of the decision tree, illustrating the model's decision-making process.
The goal is to predict the correct class for new data, and this project achieves that with the decision tree classifier. I hope this video provides valuable insights into data science and classification algorithms. Don't forget to like, comment, and subscribe for more content. Thank you for watching!
My GitHub profile :
https://github.com/data-enthusiast-shubhs
This project GitHub Repository -:
https://github.com/data-enthusiast-shubhs/Sparks_foundation.git
My LinkedIn -
https://www.linkedin.com/in/shubham-oli-12911so/
