It is good. step by step so I can understand. but unfortunately there are no subtitle.
I love how well he explained everything and made it simple to follow
par Reinhold L•
par Josafat E•
par Santiago G•
par V. V J•
par k j•
par p s•
par Rifat R•
par Ashwin P•
par George X H•
A little bit of more explanations on the autoencoders on what each components and each line of code does will help. Also a little bit of summary on what the results means for S&P data would be better too. For example, anomalies that we detected does not just mean sudden jumps in S&P closing price levels, it means the changes that are not predicted by our neural network. So if there's a big jump on index prices, if it's predicted by our RNN it wouldn't count as an anomaly.
par Amitesh S•
The project was useful. Rhyme's interface needs testing and an upgrade.
par Keith N•
should spend time on explaining LSTM and Sequence model.
par Md A R•
Good.. Need more explanation of code...
par Ben M•
Not enough description of the theory or the methods used. Found myself just writing the code out rather than understanding what I was doing which is not as useful as it could be. Make the session 1 hour 30 mins and spend the extra 30 mins letting learners know what they are actually doing rather than just following along
par Harsh K•
The instructor should explain more about the project. Specifically explaining some basic concepts first and should mention the use of projects in real life. Like how should you know, when to use this project!
par Simon S R•
hardly any explanation for the given model is provided. There are plenty of other tutorials on the web that go into more details.
par Emiel V•
The course is too short and specific to get an in depth understanding of anomaly detection with autoencoders.