Ingest, store, & analyze all types of time series data in a fullymanaged, purposebuilt database. Keep data forever with lowcost storage and superior data compression. Learn more →
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probability reviews and mentions
 [P] Any good resources which can help me with Multivariate Time Series Forecasting using Probabilistic Machine Learning?
 Is anyone here working in uncertainty estimation in neural networks?

[Q] Sociology PhD Student with Interest in Statistical Programming/Data Science
As others have said, R for academia, Python for industry. However, i'd also throw Stan into the mix, along with other PPL frameworks like Tensorflow Probability and Pyro. The latter two will require you to learn Python first, though.

What is Probabilistic Programming?
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are  Stan (https://mcstan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arvizdevs.github.io/arviz/), which can be used for all the abovementioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing

A note from our sponsor  InfluxDB
www.influxdata.com  3 Jun 2023
Stats
tensorflow/probability is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of probability is Jupyter Notebook.
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