Introduction to scikit learn
Apply Machine Learning in your projects through scikit-learn
Course Outcomes
- 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
Course Structure
28 lectures • 2h 42m total duration
About This Course
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.
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This course is interactive
Interactive courses include hands-on coding exercises to practice as you learn. You practice exercises in a VS Code like IDE without any installation/setup.
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Course Instructor
I graduated from BITS Pilani Goa Campus in 2015 with B. E. (Hons.) Computer Science and M. Sc. (Hons.) Mathematics. After graduation, I worked with Google from 2015 to 2020 with operations research te...View profile
More Courses By Krunal Patel
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What's in the course?
- 9 video lectures
- 12 hands-on-keyboard exercises
- 7 quiz exams
- GPT-4 level AI assistance
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