Laurence Moroney
Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this third course, you’ll use a suite of tools in TensorFlow to more effectively leverage data and train your model. You’ll learn how to leverage built–in datasets with just a few lines of code, use APIs to control how you split your data, and process all types of unstructured data. This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.
Instructor Details
Courses : 8
Specification: Data Pipelines with TensorFlow Data Services
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12 reviews for Data Pipelines with TensorFlow Data Services
Add a review
| Price | Free |
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| Provider | |
| Duration | 13 hours |
| Year | 2020 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Sayak P –
Very practical!
Soren J –
Some issues with notebooks. This is still in beta. Absolutely no help with the technical setup (notebooks and the Tensorflow datasets). Needs to be debug a couple of times..
Danilo C –
I’m sorry but, it does not seem realistic pipelines, it clearly show the capability of tensorflow, but real world data pipeline on my point of view is completely different from that. I was expecting something like how to handle large amounts of data coming into the cloud, or onpremise cluster, and get it into a retraining pipeline, improving the models… but was completely different… If you are expecting something like, How to retrain a large model with large amounts of new data, realtime… that is not the course for you. I love Andrew and Lawrence, but this last specialization is not at the same level from the other 3 from Deeplearning.ai, you guys should consider rethinking it using more Cloud deployment strategies with Tensorflow, like delivering APIs that requests model inference, and retrain automatically, using Google Cloud, Sagemaker, Azure whatever…, integrate it into a MLOps/DevOps model, and delivery at scale, at edge, that is the real world of deployment in my view…
Michael –
The course has a lot of practical experience and content. The reference material available, including the support is very limited. Which makes it hard to debug the code, you would literally spend days. I struggled on my on with no help whatsoever from the mentors in week 3. At least in week 4, there was some help. The balance between the quiz questions, which does not contribute in any way to the overall passing, and the practical is totally off. Maybe if we could get notes, to help us. Maybe just touch ups, but overall, Mr Laurence Moroney you are a great trainer. Looking forward to course 4.
Andrei D –
Excellent course both for Data Scientists and Machine Learning Engineers!
Thomas A –
The last exercise does not seem complete. There is too less help about solving the excercise moderators do not help.
Qi D –
good,but the last exercise is a bit tricky
Liang Chun C –
It’s a more advanced topic related to creating datasets which fit into TensorFlow data pipeline. However, lectures contain too much information per slide without highlight what the instructor was talking. A little bit hard to follow. Overall, This course include useful information and require additional time to organize all materials again. Thanks for making such an incredible course.
Evgeny K –
Unfortunately this course is extremely weak. Tons of poorly explained code and nothing else
Andras G –
Dataset creation task was more complex for me then all previous before.
Cees R –
I liked the topic and instruction of this course. I had bumped onto the notion of datasets earlier, was impatient as I needed to just resolve an issue, and skipped it. Next time I know what they are about and will be able and happy to use (including build) them. Slight minus: presentation in the video often contained some bullets that I couldn’t connect to the speech, that is, I had to choose: read or listen. Bummer: the last week’s exercise effectively required to copy paste from a notebook that was scrolled through in the video. That is silly enough in itself. What is more, for certain errors in the created code in the notebook, the grader gave a standard notification that was not helpful in resolving the identifying what coding error had been made. As the discussion showed, a good number of people me including had been struggling with this to the level of feeling helpless to resolve it. Still four stars for instructional value of the whole course, but I hope for the sake of future students that the above mentioned exercise will be replaced by a better one.
Nicholas B –
This seemed very helpful and hands on. I can’t wait to try this on my own.