Supervised Learning Models
Machine Learning
| Beginner
- 13 videos | 33m 13s
- Includes Assessment
- Earns a Badge
Supervised learning is one of the most popular techniques in machine learning. Explore supervised learning models and how to use them to solve problems.
WHAT YOU WILL LEARN
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Describe the difference between classification and regression models and the use for each of them
Describe how decision trees can be applied regression problems
Describe the cart decision tree learning algorithm and how it's different from c4.5
Describe the random forests machine learning
Use scikit learn to build a random forest model in python
Describe the logistic regression model
Use scikit learn to fit a logistic regression model -
Describe support vector machine models
Describe how to use kernel methods with support vector machines to model more complex data
Use scikit learn to train and support vector machines in python
Describe the naïve bayes classifiers and how to train them
Use scikit learn to fit a naïve bayes classifier in python
Describe different supervised learning models in python
IN THIS COURSE
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3m 8sAfter completing this video, you will be able to describe the difference between classification and regression models and when to use each of them. FREE ACCESS
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1m 55sUpon completion of this video, you will be able to describe how decision trees can be applied to regression problems. FREE ACCESS
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3. CART Decision Tree Learning2m 8sUpon completion of this video, you will be able to describe the CART decision tree learning algorithm and how it differs from C4.5. FREE ACCESS
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4. Random Forests1m 56sUpon completion of this video, you will be able to describe the random forests machine learning algorithm. FREE ACCESS
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5. Random Forests with Python3m 28sDuring this video, you will learn how to use SciKit Learn to build a random forest model in Python. FREE ACCESS
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6. Logistic Regression Model2m 7sUpon completion of this video, you will be able to describe the logistic regression model. FREE ACCESS
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7. Logistic Regression in Python3m 14sIn this video, you will learn how to use SciKit Learn to fit a logistic regression model. FREE ACCESS
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8. Support Vector Machines (SVM)1m 32sAfter completing this video, you will be able to describe support vector machine models. FREE ACCESS
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9. Kernel Methods for SVMs1m 42sUpon completion of this video, you will be able to describe how to use support vector machines with kernel methods to model more complex data. FREE ACCESS
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10. Support Vector Machines in Python3m 45sLearn how to use SciKit Learn to train and support vector machines in Python. FREE ACCESS
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11. Naïve Bayes Classifiers2m 39sAfter completing this video, you will be able to describe Na√Øve Bayes classifiers and how to train them. FREE ACCESS
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12. Naïve Bayes Classifiers in Python3m 40sLearn how to use SciKit Learn to fit a Naive Bayes classifier in Python. FREE ACCESS
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13. Exercise: Supervised Learning in Python1m 59sUpon completion of this video, you will be able to describe different supervised learning models. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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