Excelente curso que explora o ajuste fino dos hiper-parâmetros, Regularização e Otimização dos modelos de Deep Learning. Recomendo fortemente este curso, pois o professor possui uma excelente didática e os exercícios são muito claros e objetivos.

The course material was very good. The only issue I had was that the system seemed to go down once in a while, and I would have to exit and sign back into Coursera. Restarting the kernel didn't help. This would sometimes cause me to lose work.

considering the topics that are covered those are very good and detailed and as a beginner those are required to be known to every individual , especially professor andrew has put a lot of efforts in designing the course it seems , it's very nice

Thanks to the instructor and the team for creating an excellent and rigorous online course. I particularly enjoyed learning the ADAM optimizer from the ground up. The quizzes and programming assignments are also challenging and fun. Thanks again!

This course teaches how to organise training in a structured and systematic way without doing things so complicated. Also very good introduction to tensorflow a library that any data scientist that is serious about deep learning should now about.

Very useful course which helped me to organize my thoughts about how to select the model hyperparameters, how to extended the network for multiple outputs using the softmax function. Additionally the Tensorflow lab was very helpful as jump start.

After Completing this course I can now understand some of the secrets of Regularization, Batch Normalization, Learning Rate and many more thing related to Deep Learning.Assignments are very relatable to explore what you just learn in every week.

Legendary Andrew Ng strikes again! Great chapter of this Deep Learning Specialisation! Good balance of theory and must-know concepts for improving neural networks! I especially appreciated the optimization part and the tensorflow coding exercise

After completion of this course, I knew what I have to do to make my neural network to perform better and how to avoid over-fitting. And what range of values and techniques, I can use/check and how I will set my hyper-parameter more effectively.

This is awesome.

Andre Ng gives great lectures, the practical exams are easy to follow and no installation of software and other annoying bumps on the road as everything you need is running smoothly using Jupyer notebooks on preinstalled servers!

This was the best course of this series as I have observed it was awesome to learn various normalization techniques and then implement them form the scratch and then the various optimizer. But in the last programming exercise the task was less.

A important aspect of machine learning that is left untaught and ignored that is hyperparameter and optimization.This course cover them all and also the best practices .Deeplearning.ai specialization is really the best course I have ever taken.

Contents are structured in a way that it is so easy to pick up. Programming exercises are exactly in the balance that is not too hard or it isn't too easy. Learned a lot in this course especially. Thank you so much for this excellent course !!!

A good summary of Hyperparameter tuning, Regularization and Optimization. One suggestion would be to extend this course for 1-2 weeks and emphasize more on the intuitions and mathematics behind the optimizers. But again, the videos are awesome.

Simple and straight forward explanation of most helpful tools. Examples are well designed. However I feel that introduction to TensorFlow is very brief, it should have been more elaborative. Anyhow overall a well designed and well paced course.

This course taught me a lot of things that I cannot usually find in a school curriculum, yet the content are extremely useful in helping me to accelerate my algorithms. This course is super important in handling deep learning projects, I think.

Another excellent course by Proffesor Ng. Lots of material to learn but neatly organized and extends the journey from the previous course. Lots of ML/DL terminology is clarified and their place and importance shown in this course. Very useful!!

Take this course if you want to know:

1). He Initialization

2). Adam Optimization

3). Batch Normalization

4). Softmax Activation (or regression)

5). Tensor-Flow for programming Deep-net.

It is an amazing course. It is well-structured and presented.

Great course, learned a lot about hyperparamter tuning, different types of optimization methods, and regularization techniques. But, I felt more Tensorflow exercises are needed to get good grasp and use it smoothly to solve different problems.

This is just an amazing Courese in Deep Learning, about neural network optimisation by chosing optimum hyperparameter. I would recommend every boy who i really interested in learning the deep thought of deep learning to go through this course.

Understand well the fundamental and most of the hyper-parameters tuning mechanism and processes. The course has included some fundamental knowledge of using TensorFlow. It is well organized in the teaching processes and programming assignment.

Great Course. I especially like how the mathematics of Deep NNs are presented, taught and practiced, before the revelation of frameworks such as Tensorflow(in particular). This gives me a great understanding of what these frameworks are doing.

This course brings you all the details to make your neural network training works better (faster, more accurate, etc.). The materials are presented nicely (as usual), not only the formulas but also the intuition behind them as well. Very good.

Really cool course, review what i knew already. In addition learn more common optimization algos (GD with momentum, RMSprop, Adam). Get the sense of approaching the most tricky part hyperparameters tuning. Nice and smooth intro to Tensorflow.

This course has been amazing. I have learning various interesting topics such as overfitting,techniques to avoid overfitting,Different optimizers and softmax regularization. Tensorflow framework is awesome. Looking forward to learn that too.