# Alternative to Netica for Bayesian Modeling

**URL:** <https://discourse.julialang.org/t/alternative-to-netica-for-bayesian-modeling/58265>\
**Category:** Probabilistic Programming\
**Created:** [March 30, 2021, 11:19pm UTC](https://discourse.julialang.org/t/alternative-to-netica-for-bayesian-modeling/58265 "2021-03-30T23:19:44Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![erlebach1](https://avatars.discourse-cdn.com/v4/letter/e/ed655f/32.png) [@erlebach1](https://discourse.julialang.org/u/erlebach1)\
**Post date:** [March 30, 2021, 11:19pm UTC](https://discourse.julialang.org/t/alternative-to-netica-for-bayesian-modeling/58265/1 "2021-03-30T23:19:44Z")

</div>

Hi,

Does anybody know of a good package the duplicates or extends the functionality of Netica (commercial software) to model Bayesian networks? Would Forney.jl or Turing.jl be appropriate to this task? Thank you.

---

<div class="post-metadata">

**Author:** ![Storopoli](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/storopoli/32/209278_2.png) [@Storopoli](https://discourse.julialang.org/u/Storopoli)\
**Post date:** [March 31, 2021, 3:04pm UTC](https://discourse.julialang.org/t/alternative-to-netica-for-bayesian-modeling/58265/2 "2021-03-31T15:04:47Z")

</div>

Maybe Flux.jl + Turing.jl. See the Turing Tutorial about Bayesian Neural Networks: [https://turing.ml/dev/tutorials/3-bayesnn/](https://turing.ml/dev/tutorials/3-bayesnn/).