Introduction to Scikit Learn
Scikit-Learn is an essential python library for all machine learning applications and solutions.
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About this course
Scikit-learn, previously known as scikits.learn is a NumFOCUS fiscally sponsored project and a free software library in machine learning to support Python programming language. It includes various features to interoperate with Python numerical and scientific libraries such as NumPy and SciPy. These features include classification, regression, and clustering algorithms like support vector machines (SVM), gradient boosting, k-means, random forests and DBSCAN.
This free Scikit-Learn course will help you understand the subject better by walking through various concepts starting from the introduction and following with demonstration in Python, guiding you through installation, its support for algorithms, applications, advantages and disadvantages. With these concepts, you will be able to understand various metrics that add one more skill to your bucket for your journey towards the Data Science domain.
Great Learning proffers various Postgraduate Programs in Data Science domains. You can register for the best online Data Science course and earn a certificate from a renowned university. As an ed-tech organization, we aim to empower our learners by helping them achieve their dream careers. We cater to enthusiasts willing to bring global transition in their desired domain. Join us to explore our programs with millions of learners across the globe. Happy learning!
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Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What is Scikit-learn used for?
Scikit-learn comes under the Machine Learning library for Python. It is developed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. It can be used for:
- Data Preprocessing
- Dimensionality Reduction
- Supervised Learning
- Unsupervised Learning
- Model Selection
Is Scikit-learn hard to learn?
Scikit-learn is not difficult to learn, but it does require some prior knowledge of machine learning concepts. The scikit-learn library is well-documented, and there are many resources available to help users get started which makes it easier for beginners to start learning it. You can start with the basics of Scikit-learn by enrolling in Great Learning’s free Scikit-learn course.
Should I learn Scikit-learn or TensorFlow?
The reply to this query depends on your specific needs and goals. If you want to learn Machine Learning to build models and perform predictions, then you should learn Scikit-learn. If you desire to learn Machine Learning in order to be able to build Deep Learning models, then you should learn TensorFlow. If you are more interested in Scikit-learn, enroll in Great Learning’s free Scikit-learn course and make your basics stronger.
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