Machine-Learning using scikit learn
- Offered byDataCamp
Machine-Learning using scikit learn at DataCamp Overview
Machine-Learning using scikit learn
at DataCamp
Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data
Duration | 4 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Machine-Learning using scikit learn at DataCamp Highlights
Machine-Learning using scikit learn
at DataCamp
- Earn a Certificate after completion of the course
- Practical learning with Assesments and Exercises
Machine-Learning using scikit learn at DataCamp Course details
Machine-Learning using scikit learn
at DataCamp
Skills you will learn
More about this course
- In this course, students will learn how to use Python to perform supervised learning, an essential component of machine learning
- They will learn how to build predictive models, tune their parameters, and determine how well they will perform with unseen data—all while using real world datasets
- They will be using scikit-learn, one of the most popular and user-friendly machine learning libraries for Python
Machine-Learning using scikit learn at DataCamp Curriculum
Machine-Learning using scikit learn
at DataCamp
Classification
Supervised learning
Which of these is a classification problem
Exploratory data analysis
Numerical EDA
Regression
Introduction to regression
Which of the following is a regression problem
Importing data for supervised learning
Exploring the Gapminder data
Fine-tuning your model
How good is your model
Metrics for classification
Logistic regression and the ROC curve
Building a logistic regression model
Preprocessing and pipelines
Preprocessing data
Exploring categorical features
Creating dummy variables
Regression with categorical features
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Machine-Learning using scikit learn
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