Torch is another great library for developing Deep Learning applications. Several useful libraries extend its codebase, all of which are backed by an active community.

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Torch is a LuaJIT library that was developed by Ronan Collobert and Soumith Chintala of Facebook, Clement Farabet of Twitter, and Koray Kavukcuoglu of Google DeepMind. With Torch, you can configure a deep net by selecting options for certain hyper-parameters, and then you can access the deep net within your code.

Several libraries extend the functionalities offered by Torch. The CUDA library Cutorch provides GPU support. Other libraries like NN, Cephes, DP, and NNgraph provide you the necessary tools to build nearly every kind of deep net.

Have you ever used the Torch library in one of your Deep Learning projects? Please comment and share your experiences.

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Welcome to part 2 of the web scraping with Beautiful Soup 4 tutorial mini-series. In this tutorial, we're going to talk about navigating source code to get just the slice of data we want.

Tutorial code: https://pythonprogramming.net/....navigating-pages-scr

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