Introduction to scikit learn
Apply Machine Learning in your projects through scikit-learn
Goals
- Basics of ML concepts
- Preprocessing data using scikit learn
- Classifiers in scikit learn
- Model evaluation using scikit learn
- Hyperparameter tuning using scikit learn
- Regression using scikit learn
Description
Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. Scikit-Learn is characterized by a clean, uniform, and streamlined API. It also provides various tools for model fitting, data preprocessing, model selection and evaluation, and many other built-in machine learning algorithms and models. In this course, I provide a basic introduction to scikit learn and machine learning.
You do not need to have a background in machine learning. However, knowledge of python is required for this course.
By the end of this course, you should be able to apply basic ML models in your application using scikit-learn.
Course Structure
28 lectures • 02:42:24 total duration
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Your Course Instructor
Krunal Patel
Never stop learning.
What you will get:
- 2 hours+ on-demand video content
- 12 hands-on-keyboard exercises
- This + all other courses access (Pro)
- 24x7 mentorship available
- In-browser IDE to practice
- Certificate of completion
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- HD video content
- Certificate of completion
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- 24x7 mentorship support
- 100+ projects to practice
- In-depth project feedback