The last exercise for TensorFlow was the most fun of all the exercises! Explanations were good, and I still had the opportunity to google documentation to finish some of the functions

I felt like this course gave me a very solid foundation in improving my deep learning models. It tries to touch on the major topics to give you a starting point for your own research.

I love this course. It has many in-depth tips and advices based on many real life experiences. Many suggestions can be applied directly into solving difficult Deep Learning practices.

This is much needed course with great content on improving neural networks which is rarely available in any other online course. Suggestions from andrew Ng's experience is invaluable.

the course is great, truly continuation of the first course. starting with hyperparameters tuning then how to speed up the process, finally use DL framework to efficiently build model

Absolutely necessary! Although they were stronger on Regularization and Optimization than on Hyperparameter tuning, one cannot go about using ML/DL without those concepts amalgamated.

A clear explanation of a difficult subject with an emphasis on being able to create and to understand your own neural networks.- Plus in this module how to make them work efficiently.

Excellent course after the preliminary one. You get used to the style of programming that is intended to be the best for someone who's starting out. Can't wait to go to the next one!

great course. Love the instructor. Andrew Explained stuff so better than other literature available on internet. learned a lot about optimization. thanks for such a wonderful course.

Improving my Knowledge using this course. I am happy to be able to learn these course materials by Honorable Andrew Ng.

Thank you for such a good effort for passing on your knowledge.

Fantastic course. I love how much high-level intuition Andrew aims to convey, without leaving out any of the low-level details that I consider completely crucial to my understanding.

This course is one of the most important for actually doing deep learning. I also liked the hands-on exercises that (again) improved my knowledge of things like numpy and tensorflow.

This continues to be a very well done series of courses. The sections are cohesive and grouped in a way that makes it easy to learn the concepts needed before progressing. Thank you!

A great value addition to the first deep learning course in the module. I liked going into the details of hyperparameters and good way to get started with tensorflows. Just loved it!

Hyperparameter tuning and selection of the best learning algorithm are topics which are frequently less understood. This course teaches a systematic approach to thinking about these.

This course gives me a deep understanding of how to tune hyper parameter, how to implement regularization and optimization. It really makes me move a big step forward in the AI way.

This course alongside the whole specialization helped me a lot with my bachelor's thesis! I thank Andrew and deeplearning.ai for all of the excellent information they have provided!

The course is fruitful, it contains a lot of valuable contents. I feel like it's useful for ML in general not just NN. It's totally recommended for anyone interested in applying NN.

Great in-depth lectures, with lots of example. I am able to understand the core concepts and with tensorflow will be able to implement them as well.

Thanks a lot to to the instructor

Give good understanding about optimization of Neural Networks. Covers almost all the techniques required for beginners.Better If you can update the course to include new algorithms.

It was extremely helpful for me to prepare a strong base towards neural networks. Thank you for much needed intro on Tensorflow. I feel more confident on working with ML frameworks.

Yet an amazing course by deeplearning.ai. The course transfers practical aspects of machine learning of optimizing neural nets to using the industry relevant framework - TensorFlow.

This course is a must-do for deep learning practitioners as it teaches about the most important parts of deep learning which are essential to understand to build an efficient model.

Very helpful for if you like to apply NNs. Gives a good overview about what is really effective for learning. A well balanced insight into essential and effective tuning algorithms.

Great course but it's not well covered the use of dev set data in the code exercises. Cross Validation is not teach how to code so there is a gap between theory and coding practice.