IRIS Flower Classification using Scikit-Learn Generalised models: An example of Multi-Class…

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IRIS Flower Classification using Scikit-Learn Generalised models: An example of Multi-Class Classification in Python — Data Science Recipe 005

In this Data Science Recipe, the reader will learn

1. Different types of Machine Learning problems.
2. How to organise a Predictive Modelling Machine Learning project.
3. Implementation steps in Applied Machine Learning project.
4. Different elements of data used for predictive modelling.
5. How to install Python and MySQL.
6. How to load Dataset from RDBMS.
7. How to summarize and visualize Dataset.
8. How to implement Generalised Models for Multi-Class Classification in Python.
9. How to train a model and perform Cross Validation (CV).
10. How to compare CV results of different models/algorithms.
11. How to report results for trained models and compare.
12. How to implement an end-to-end Data Science Project using MySQL and Python.

What is Machine Learning?

Machine learning is the science of getting computers to act without being explicitly program. It is a subset of AI: Artificial Intelligence. Predictive modelling is a branch of Machine Learning that particularly deals with tabular data to explicitly find patterns and/or insights from the data available.

To learn more, Download FREE data science recipes for Beginners.

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