Time Series Analysis and Forecasting with Python (Udemy.com)

I've got other course talking about RNN/LSTM, however, this one beats others by explaining ARIMA and LSTM in a easy understand but detailed enough manner. The primer in numpy, pandas and matplotlib is also good but don't expect too much. The topic is too big to discuss in just a few hours.

El curso es bueno, el profe explica bastante bien, sin embargo siento que sobretodo al final no profundiza demasiado en la teoría (aunque esto lo entiendo, pues haría el curso demasiado pesado); ni tampoco en el código. Algunas funciones las utilizaba, sin explicar muy bien que hacia cada uno de los parámetros, pero explicando el resultado que obtiene. Si ya has visto algo de Pandas, Numpy y Matplotlib, recomiendo saltarse esa parte. Aunque no seas experto el código es lo suficientemente auto-explicativo.

overall, it's just an intro to forecasting with an example, the part teaching the LSTM conecpt is not well done, and also i wish it would get into hyperparameter selection and coding.

The instructor knows the code well but the lecture and presentation is not the best for learning new concepts like SARIMAX and LSTM. He may want to collaborate with professionals who do lectures /presentations for a more cohesive experience. Audio and font size are below average I've noticed he responds to certain questions with details and others with vagueness or redirect.

Until now, it is exactly what I needed! A perfect match for me. I was searching for a method for gas consumption forecasting. The final example was for electricity consumption. I suppose that if last example would have been on gas consumption, that would imply an overfitting for my needs :)

Interesting insights but the format is inefficient: should use jupyter notebooks. Some basic errors like fitting a different scaler for the test set... Presenting different methods with different data sets is also disappointing. There is no sense of benchmarking: which one works better?

The course is one of the few that touch exactly to my required learning target, the instructor is giving a step by step teaching approach that would suit even the new comers to deep learning. One thing needs to be improved: The resolution of the videos, when start working with the spyder coding need to be enhanced, I find it too small and too difficult to read.

Really Nice course. Most of the Timeseries course available dont touch LSTM topic. LSTM has been wonderfully explained with python code line by line. Without explanation it is absolutely impossible to guess what is happening and what we are trying to do. It is little difficult also. I have heard the video again and again with pause to understand. But at the end all makes sense. Only one problem with the video is that codes font is very small and very difficult to see and follow. I have copied the codes files and then had to jump between video and code file to understand. Kindly use some zoom feature to show the code when you are typing. Looking forward to see more amazing courses from you.

I had participated in ' Data science and machine learning A-Z' course a few months ago. This course is as amazing as that course and that's the reason I enrolled in this course. Beside this, the instructor clearly explain concepts, also this project based course made valuable opportunity for those who want to learn practically.

until now everything is good but I'm confusing about seasonal and other graph ,it seams that I need study some paper about definition of these expression or i try to continue our sessions to reach an real example , I mean know these expression by real example