[Download] Feature Selection for Machine Learning For Free
What you’ll learn
- Learn about filter, embedded and wrapper methods for feature selection
- Find out about hybdrid methods for feature selection
- Select features with Lasso and decision trees
- Implement different methods of feature selection with Python
- Learn why less (features) is more
- Reduce the feature space in a dataset
- Build simpler, faster and more reliable machine learning models
- Analyse and understand the selected features
- Discover feature selection techniques used in data science competitions
Requirements
- A Python installation
- Jupyter notebook installation
- Python coding skills
- Some experience with Numpy and Pandas
- Familiarity with Machine Learning algorithms
- Familiarity with scikit-learn
Who this course is for:
- Beginner Data Scientists who want to understand how to select variables for machine learning
- Intermediate Data Scientists who want to level up their experience in feature selection for machine learning
- Advanced Data Scientists who want to discover alternative methods for feature selection
- Software engineers and academics switching careers into data science
- Software engineers and academics stepping into data science
- Data analysts who want to level up their skills in data science