In the second course of Machine Learning Engineering for Production Specialization, you will build data pipelines by gathering, cleaning, and validating datasets and assessing data quality; implement feature engineering, transformation, and selection with TensorFlow Extended and get the most predictive power out of your data; and establish the data lifecycle by leveraging data lineage and provenance metadata tools and follow data evolution with enterprise data schemas.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Machine Learning Engineering for Production (MLOps)
von

Über diesen Kurs
• Some knowledge of AI / deep learning
• Intermediate Python skills
• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
Was Sie lernen werden
Identify responsible data collection for building a fair ML production system.
Implement feature engineering, transformation, and selection with TensorFlow Extended
Understand the data journey over a production system’s lifecycle and leverage ML metadata and enterprise schemas to address quickly evolving data.
Kompetenzen, die Sie erwerben
- ML Metadata
- Convolutional Neural Network
- TensorFlow Extended (TFX)
- Data Validation
- Data transformation
• Some knowledge of AI / deep learning
• Intermediate Python skills
• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
Lehrplan - Was Sie in diesem Kurs lernen werden
Week 1: Collecting, Labeling and Validating Data
Week 2: Feature Engineering, Transformation and Selection
Week 3: Data Journey and Data Storage
Week 4 (Optional): Advanced Labeling, Augmentation and Data Preprocessing
Bewertungen
- 5 stars60,23 %
- 4 stars21,63 %
- 3 stars9,81 %
- 2 stars4,99 %
- 1 star3,32 %
Top-Bewertungen von MACHINE LEARNING DATA LIFECYCLE IN PRODUCTION
Interesting material. There are quite a lot of typos and many code snippets are directly from the tfx manual pages however the instructions provided and logic of the course is clear.
The course is exciting. Lab and exercises are informative, but the answer to the quizzes are a little ambiguous.
It's a new course so sometimes there are mistakes in the translations or there is something off in the assignment's grading, but the content is great. :)
excellent course. Nice to see how we can detect data drift and skew drift
Über den Spezialisierung Machine Learning Engineering for Production (MLOps)

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