Chevron Left
Back to Machine Learning Data Lifecycle in Production

Learner Reviews & Feedback for Machine Learning Data Lifecycle in Production by DeepLearning.AI

56 ratings
7 reviews

About the Course

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. Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles to help you develop production-ready skills. Week 1: Collecting, Labeling, and Validating data Week 2: Feature Engineering, Transformation, and Selection Week 3: Data Journey and Data Storage Week 4: Advanced Data Labeling Methods, Data Augmentation, and Preprocessing Different Data Types...
Filter by:

1 - 8 of 8 Reviews for Machine Learning Data Lifecycle in Production

By Riju M

Jun 15, 2021

The labs and assignments were interesting but the lectures, content videos were not engaging.

By Tyler G

Jun 11, 2021

A somewhat disappointing and misleading followup to the excellent first course in this specialization. I​t's heavily focused on shallow learning on structured data, which is not at all what I think of when I think of the challenges in prod ML.

TFX feels more like a solution to technologies that were available well before the deep learning revolution. T​here are certainly some useful, albeit complicated, tools coming out of google/tensorflow. We'll see if TFX sticks or just becomes another tensorflow.estimator in the shadow of keras.

By Aadidev S

May 16, 2021

This was quite exciting! A lot of new, innovative content in the TFX libraries along with all the theoretical background necessary for determining when to use each component in the data life-cycle, highly recommend!

By Fernandes M R

Jun 19, 2021

Its good, I think was a little difficult because TensorFlow, but it was very explicative.

By Chandan k

Jun 22, 2021

A good course indeed to pursue my dream job !

By Manuja

Jun 9, 2021

Fantastic course

By Bharath P

May 29, 2021

excellent course. Nice to see how we can detect data drift and skew drift

By Germán G

May 28, 2021

Traté en varios navegadores de enviar mi trabajo para ser sometido a evaluación, sin éxito. No obtuve respuesta ni soporte.

El contenido es interesante pero el soporte y habilitación no está al nivel de lo requerido: es lamentable que no reembolsen.