Modeling Irises plants using ML in Python | Medium
According to florgeous.com, “Irises have always been a favorite flower choice among florists and gardeners, and I don’t see any reason why they shouldn’t be. These perennials produce unique and undeniably beautiful blooms that carry different meanings and rich history.”
“Although iris flower bouquets or iris cut flowers are often blue, purple, white, or yellow, there are, in fact, a plethora of colors that fascinating garden irises offer. So, if you’re planning to add a splash of color in your home, then iris plants are worth considering.”
As a result of that, we have a dataset about Iris and
Today I’m going to explain building a model training in Python using machine learning as simple as possible. In my humble opinion, first off we will load popular libraries such as pandas,matplotlib, and sklearn
I will provide some definitions and introductions of important concepts and libraries such as Data Science and Machine Learning along withpandas, matplotlib and sklearn libraries before divining into the article.
According to datarobot, “Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights which analysts and business users can translate into tangible business value.”
According to https://www.expert.ai/blog/machine-learning-definition/, “Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.”
According to Pandas, “pandas is a fast, powerful, flexible and easy to use open-source data analysis and manipulation tool,
built on top of the Python programming language.”
According to https://matplotlib.org/, “Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.”
According to https://scikit-learn.org/stable/, “Simple and efficient tools for predictive data analysis. Accessible to everybody, and reusable in various contexts. Built on NumPy, SciPy, and matplotlib. Open source, commercially usable — BSD license.”
Secondly, as you might know, we load the data so we can build a trained model upon it.
In addition, we print the shape of the dataset along with the printing head, describe the method, etc
Now, we come to plotting, displaying, and visualizing the loaded dataset in general along with training and testing the model itself.
Finally, you can see below the results and the figures based on the code we run
Finally, you can check the code on Gihub
https://github.com/nasserfq/Modeling-Irises-plants-using-ML-in-Python
