Our Next Live Session: Time Series Forecasting with Deep Learning Techniques

We are excited to announce that our next live session will take place on Sunday, May 10th at 6 p.m. in the evening, and it will be accessible to all of our course-registered students through the desktop app. This live session will last for two to two-and-a-half hours, depending on how much we can cover within that timeframe. We have a bunch of very interesting topics lined up for this session, and we aim to finish by 8:00 p.m., so you'll have plenty of time to ask questions and engage with the material.

The topic of discussion for this live session is going to be time series forecasting using deep learning techniques like LSTM's and GRU's. We will begin by doing code walkthroughs, but this time we'll focus on implementing these techniques specifically for time series forecasting problems. Our approach will involve starting with simpler problems and gradually moving towards more complex variations. It's worth noting that the tricky part of working with LSTM's and GRU's is posing the problem carefully, so we'll take three different slightly different types of time series forecasting problems and solve them by formulating the problem very carefully and then writing code in TensorFlow 2.0 and Keras to solve the problem using these scenarios.

For this live session, we assume that you have a strong foundational understanding of LSTM's, GRU's, and RNNs in general, as well as having gone through our previous live sessions and code walkthroughs on TensorFlow and Keras. We won't repeat concepts or code snippets that we've already covered earlier, so please come prepared to dive into the material. Our goal is to solve multiple variations of time series forecasting problems within this two-to-two-and-a-half-hour timeframe, using the same format as our previous sessions. During the session, we'll spend about 9,200 minutes going through the code line by line and answering all your questions on our Slack miscellaneous channel.

We're looking forward to seeing you on May 10th at 6:00 p.m., which is just a few days away. It's been a productive live session so far, but we have plenty more to cover in this final installment.

"WEBVTTKind: captionsLanguage: enhi friends our next live session will be at 6 p.m. in the evening on the 10th of May which is the coming Sunday so this live session will be accessible to all of our course registered students while the desktop app and this live session will be a two to two-and-a-half hour live session based on how much we can cover in two or two and half hours I have a bunch of very interesting topics that we want to cover so probably we will finish the session between 8:00 and 8:30 p.m. so now that what is the topic of discussion so again we will continue on the same path of doing code walkthroughs but this time we'll do a code walkthrough of how to do time series forecasting using deep learning techniques like L STM's and gr use so here what we will do is we'll start with simpler time series forecasting problems solve them using simple l STM's and gr use and then we will graduate and move toward slightly more complex variations again please understand that the tricky part with LSD ms and gr use is posing the problem carefully so that's why what we'll do is we'll take three different slightly different types of time series forecasting problems and solve all of them by formulating the problem very carefully and then writing code in tensorflow 2.0 and caris to solve the problem using lsdm scenarios so for this live session the prerequisites would be the r NN Celestials and gr use that we've already covered in the course videos the theoretical part also some code walkthrough that we have in the course videos and the previous live sessions that we have already done on tensorflow and caris so i'm going to assume that you are strong with the basic foundational understanding of LS tiems gr use and RN ins in general and you have gone through the previous live sessions and the code snippets that we already have in the course videos so that we don't have to spend time repeating the same concepts and code snippets that we have already covered earlier so again please come prepared so that we can actually solve multiple variations of timeseriesforecasting problems in a two to two-and-a-half hour live session and just like the previous sessions will follow the same format we spend about 9,200 minutes going through the code line by line and spending sufficient time to answer all the questions that you have on our slack miscellaneous channel so see you on the 10th of May which is the coming Sunday at 6:00 in the eveninghi friends our next live session will be at 6 p.m. in the evening on the 10th of May which is the coming Sunday so this live session will be accessible to all of our course registered students while the desktop app and this live session will be a two to two-and-a-half hour live session based on how much we can cover in two or two and half hours I have a bunch of very interesting topics that we want to cover so probably we will finish the session between 8:00 and 8:30 p.m. so now that what is the topic of discussion so again we will continue on the same path of doing code walkthroughs but this time we'll do a code walkthrough of how to do time series forecasting using deep learning techniques like L STM's and gr use so here what we will do is we'll start with simpler time series forecasting problems solve them using simple l STM's and gr use and then we will graduate and move toward slightly more complex variations again please understand that the tricky part with LSD ms and gr use is posing the problem carefully so that's why what we'll do is we'll take three different slightly different types of time series forecasting problems and solve all of them by formulating the problem very carefully and then writing code in tensorflow 2.0 and caris to solve the problem using lsdm scenarios so for this live session the prerequisites would be the r NN Celestials and gr use that we've already covered in the course videos the theoretical part also some code walkthrough that we have in the course videos and the previous live sessions that we have already done on tensorflow and caris so i'm going to assume that you are strong with the basic foundational understanding of LS tiems gr use and RN ins in general and you have gone through the previous live sessions and the code snippets that we already have in the course videos so that we don't have to spend time repeating the same concepts and code snippets that we have already covered earlier so again please come prepared so that we can actually solve multiple variations of timeseriesforecasting problems in a two to two-and-a-half hour live session and just like the previous sessions will follow the same format we spend about 9,200 minutes going through the code line by line and spending sufficient time to answer all the questions that you have on our slack miscellaneous channel so see you on the 10th of May which is the coming Sunday at 6:00 in the evening\n"