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Getting started in scikit learn with the famous iris dataset

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4.3
4 Reviews
AnusreeRamu

Very easy to understand 2025-06-11

Arya Ghose

nice 2025-06-04

Christian Chileshe

Very good course. 2025-06-04

31Ankita Lod

very help full platform 2025-05-31

Varsha

Good 2025-05-31

CHINNI VENKATA KRISHNA

Good 2025-05-30

Akshat pal

Q 2025-05-28

DHANUJA. A

Good 2025-05-27

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Course Description

Machine learning in python, in this course we will learn about machine learning in Python, covering both theory and practical implementation. We will explore supervised and unsupervised learning, classification, regression, clustering, and dimensionality reduction using powerful Python libraries such as scikit-learn, pandas, NumPy, and Matplotlib. You will gain hands-on experience in preparing datasets, training models, evaluating performance, and improving accuracy using techniques like cross-validation and hyperparameter tuning. Whether you are predicting outcomes, discovering patterns, or building smart applications, this course will guide you through the core concepts and help you apply them effectively. By the end, you'll be able to build machine learning models from scratch, interpret their outputs, and deploy your solutions confidently in real-world scenarios. No prior ML experience needed—just basic Python knowledge. Data School
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