One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.
About this Course
What you will learn
Use the basic components of building and applying prediction functions
Understand concepts such as training and tests sets, overfitting, and error rates
Describe machine learning methods such as regression or classification trees
Explain the complete process of building prediction functions
Skills you will gain
- Random Forest
- Machine Learning (ML) Algorithms
- Machine Learning
- R Programming
Syllabus - What you will learn from this course
Week 1: Prediction, Errors, and Cross Validation
Week 2: The Caret Package
Week 3: Predicting with trees, Random Forests, & Model Based Predictions
Week 4: Regularized Regression and Combining Predictors
- 5 stars66.44%
- 4 stars22.33%
- 3 stars6.89%
- 2 stars2.51%
- 1 star1.80%
TOP REVIEWS FROM PRACTICAL MACHINE LEARNING
Great course. Only missing piece is the working information / maths behind the models. But as the name suggests it teaches practical approach towards machine learning.
recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course
Awesome course. Would recommend it, but only to those who have a bit of stats and R background. This definitely helped me get a solid enough understanding of using R for machine learning.
It was like opening up a door to a whole new world. I have discovered new tools that I will thoroughly enjoy to use for the exploration of data and for predictions. Thanks Team Coursera !
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