darts VS Mosh

Don't use an LSTM. Get up to date with SoTA methods and read the papers in the field. LSTMs are not the way forward. Read the papers I suggested. It would be very useful to come to grips with both the Time Series Repository (https://github.com/thuml/Time-Series-Library) and Darts (https://github.com/unit8co/darts) as these are widely used for research and in industry.

As others have pointed out, Prophet is not a particularly good model for forecasting, and has been superseded by a multitude of other models. If you want to do time series forecasting, I'd recommend using Darts: https://github.com/unit8co/darts. Darts implements a wide range of models and is fairly easy to use.

The problem with time series forecasting in general is that they make a lot of assumptions on the shape of your data, and you'll find you're spending a lot of time figuring out mutating your data. For example, they expect that your data comes at a very regular interval. This is fine if it's, say, the data from a weather station. This doesn't work well in clinical settings (imagine a patient admitted into the ER -- there is a burst of data, followed by no data).

That said, there's some interesting stuff out there that I've been experimenting with that seems to be more tolerant of irregular time series and can be quite useful. If you're interested in exchanging ideas, drop me a line (email in my profile).

3. darts

Looking forward to checking this out! How does this compare with darts[1]?

[1] https://unit8co.github.io/darts/

Darts is an open-source Python library by Unit8 for easy handling, pre-processing, and forecasting of time series. It contains an array of models, from standard statistical models such as ARIMA to deep neural networks. https://unit8co.github.io/darts/

active support

The new Forecast menu, featuring the open-source Darts Time Series library, offers script-friendly functionality. It's also easy to use. Don't have any data to load yet? Enter through the Stocks or Crypto menus.

I would recommend Darts in Python [1]. It's easy to use (think fit()/predict()) and includes

* Statistical models (ETS, (V)ARIMA(X), etc)

* ML models (sklearn models, LGBM, etc)

* Many recent deep learning models (N-BEATS, TFT, etc)

* Seamlessly works on multi-dimensional series

* Models can be trained on multiple series

* Many models offer rich support for probabilistic forecasts

* Model evaluation is easy: Darts has many metrics, offers backtest etc

* Deep learning scales to large datasets, using GPUs, TPUs, etc

* There's even now an explainability module for some of the models - showing you what matters for computing the forecasts

* (coming soon): an anomaly detection module :)

* (also, it even include FB Prophet if you really want to use it)

Warning: I'm probably biased because I'm Darts creator.

[1] https://github.com/unit8co/darts

If you haven’t already, and I know this doesn’t hold up for GUI emacs or vim, but consider running them through https://mosh.org/

FWIW, I wouldn't try to parse escape sequences "directly" from the input bytestream -- it's easy to end up with annoying bugs. Longer-term it's probably better to separate the logic e.g.:

- First step (for a UTF-8-input terminal emulator) means "lexing" the input bytestream as UTF-8 into a stream of USVs, which involves some subtleties (https://github.com/mobile-shell/mosh/blob/master/src/termina...).

- Second step is to run the DEC parser/FSM logic on the sequence of USVs, which is independent of the escape sequences (https://vt100.net/emu/dec_ansi_parser ; https://github.com/mobile-shell/mosh/blob/master/src/termina...).

- And then the third step is for the terminal to execute the "dispatch"/"execute"/etc. actions coming from the FSM, which is where the escape sequences and control chars get implemented (https://github.com/mobile-shell/mosh/blob/master/src/termina...).

Without this separation, it's easier to end up with bugs where, e.g., a UTF-8 sequence or an ANSI escape sequence is treated differently when it's split between multiple read() calls vs. all in one call.

Btw, you can use mosh to hide the latency of SSH. https://mosh.org/

I've been using Kitty's SSH features for as long as I can remember but I recently setup Mosh and I really like how it doesn't drop connections and supports roaming.

I am surprised many people write about ssh into a server. Mosh[1] feels more responsive and it also supports longer sessions.

[1] - https://mosh.org/

Also they support Mosh which I install on my servers. It's way better than plain ssh when you're on mobile networks and wifi, especially with connections that are unreliable or bandwidth-constrained.

I’ve recently been experimenting with MoSH (Mobile Shell). Basically think SSH but with UDP - so more resilient to shoddy network conditions, roaming access points, etc.

If it is not for production (e.g. running as a daemon or a server) and you only care about the development, another ad-hoc way is using screen/tmus-like software incl. byobu, and combine it with mosh.