Enroll Course: https://www.coursera.org/learn/feature-engineering-jp
In the world of machine learning, the importance of feature engineering cannot be overstated. If you’re looking to enhance the accuracy of your ML models and learn how to extract the most effective features from your datasets, the Coursera course ‘Feature Engineering 日本語版’ is an excellent choice. This course provides a comprehensive overview of Vertex AI Feature Store and dives deep into the intricacies of feature engineering.
### Course Overview
The course begins with an introduction to the objectives and structure, setting the stage for what learners can expect. It then transitions into a detailed exploration of Vertex AI Feature Store, a crucial tool for managing and utilizing features effectively.
One of the standout modules focuses on transforming raw data into meaningful features. This phase is often the most challenging in ML projects, and the course equips you with the necessary domain knowledge to create features that enhance the performance of machine learning algorithms.
### Key Modules
– **Feature Engineering Basics**: Understand the differences between machine learning and statistics, and learn how to perform feature engineering using BigQuery ML and Keras.
– **Preprocessing and Feature Creation**: Gain insights into Apache Beam and Dataflow, technologies that complement each other in building and executing preprocessing and feature engineering tasks.
– **Feature Cross – TensorFlow Playground**: Discover how feature crossing has become a vital tool in modern machine learning methods and learn to identify the types of problems where it can be beneficial.
– **Overview of TensorFlow Transform**: Explore the tf.Transform library for preprocessing data in TensorFlow, including normalization, integerization, and bucketing based on observed data distributions.
### Hands-On Labs
The course is not just theoretical; it includes practical labs that allow you to apply what you’ve learned using real-world tools like BigQuery ML, Keras, and TensorFlow. This hands-on experience is invaluable for solidifying your understanding of feature engineering concepts.
### Conclusion
Overall, ‘Feature Engineering 日本語版’ is a well-structured course that balances theory with practical application. Whether you’re a beginner or looking to refine your skills, this course will provide you with the knowledge and tools necessary to excel in feature engineering and improve your machine learning models. I highly recommend it to anyone interested in advancing their understanding of machine learning and feature engineering.
### Tags
1. Feature Engineering
2. Machine Learning
3. Vertex AI
4. TensorFlow
5. BigQuery ML
6. Data Science
7. Keras
8. Online Learning
9. Coursera
10. Japanese Course
### Topic
Feature Engineering in Machine Learning
Enroll Course: https://www.coursera.org/learn/feature-engineering-jp