Feature engineering is the most important aspect of machine learning. You know that every day you put off learning the process, you are hurting your model’s performance. Studies repeatedly prove that feature engineering can be much more powerful than the choice of algorithms. Yet the field of feature engineering can seem overwhelming and confusing.
This course offers you the single best solution. In this course, all of the recommendations have been extensively tested and proven on real-world problems. You’ll find everything included: the recommendations, the code, the data sources, and the rationale. You’ll get an over-the-shoulder, step-by-step approach for every situation, and each segment can stand alone, allowing you to jump immediately to the topics most important to you.
By the end of the course, you’ll have a clear, concise path to feature engineering and will enable you to get improved results by applying feature engineering techniques on your own datasets.
Target Audience
Anyone who wants to build faster, more accurate machine learning models will benefit. This course assumes that you have a basic familiarity with Python as well as machine learning concepts. The content covers material for beginners through to experts.
Business Outcomes
- Get expert knowledge of feature engineering techniques for different datasets such as videos, text, images, and audio samples
- Uncover and execute feature extraction with detailed deep-learning techniques
- Discover how to perform feature engineering on unsupervised learning and semi-supervised learning
