Step by step guide in mastering Scikit-Learn (2021)
Learn the basics of Data Science and Machine Learning with this comprehensive course. From data analysis to creating your own models, you’ll gain hands-on experience using Scikit-Learn. Suitable for beginners, this course covers everything from choosing estimators to improving model results. Start your journey in creating your own models today.
What you’ll learn
- Basics of Data science and Machine learning
- Create their own Data model and prediction modelling
- Classification and Regression Model prediction
End to end Implementation of Data science and Machine Learning model using Scikit-Learn(SKLearn)
From Data analysis and gathering to creating your own modelling will be covered as part of this course.
This course covers the entire workflow of Scikit-Learn to create a model solving the real-life problem.
Also explained Pandas, Numpy, Matplotlib, Seaborn function used along with this course.
Covered in detail on creating model for Classification and regression helping users to solve supervised learning problems in detail.
Used 6+ Datasets for creating model and contains detailed explanation on how to choose estimators based on data available.
Explained the option of improving the results by changing parameters and Hyper-parameter in a model.
Covers in detail about:
Getting data ready
Choosing estimators
Fitting the data
Predicting values
Evaluation of results
Improving the results of the model
Saving the model.
Who this course is for:
- Beginners of programming
- Willingness in learning to create their own modelling
User Reviews
Be the first to review “Step by step guide in mastering Scikit-Learn (2021)”
You must be logged in to post a review.
There are no reviews yet.