- Iris flowers come in three species: setosa, versicolor, and virginica, each distinguished by their measurements.
- Your mission is to train a machine learning model capable of classifying iris species based on their measurements.
- Utilize the Scikit-learn library dataset or download it here for this exciting iris flower classification project.
- Dive into analyzing the unemployment rate, a critical metric reflecting the percentage of unemployed individuals in the total labor force.
- Given the significant impact of Covid-19 on unemployment rates, this project presents a meaningful data science endeavor.
- Explore the factors influencing car prices, including brand goodwill, features, horsepower, and mileage.
- Immerse yourself in the realm of machine learning by training a car price prediction model in this research-intensive project.
- Tackle the ubiquitous challenge of spam emails using Python.
- Build an email spam detector and employ machine learning to train the model in distinguishing between spam and non-spam emails.
- Venture into the realm of sales prediction, a critical aspect for product and service-based businesses.
- Leverage machine learning in Python to predict future sales, considering factors such as advertising spend, target audience, and advertising platforms.
Embark on these diverse and engaging tasks to enhance your skills in data science and machine learning. Happy coding! 🚀💻