Marco Friaz
1c0826e55b
**Description** This change checks the sagemaker session if there is a default_bucket_prefix set. If a default bucket prefix is specified, it is append it to the s3 path. This was done for hyperparameter_tuning, introduction_to_amazon_algorithms and sagemaker-pipelines sample notebooks. This ensures sample notebooks that utilize s3, works in SageMaker Unified Studio. Co-authored-by: Marco Friaz <marfriaz@amazon.com>
Latent Dirichlet Allocation and Topic Modeling
An introductory notebook on using Amazon SageMaker to train and use LDA models.
References
The example used in these notebooks come from the following paper:
- Thomas Griffiths and Mark Steyvers. Finding Scientific Topics. Proceedings of the National Academy of Science, 101(suppl 1):5228-5235, 2004.
For more details about LDA and information about the algorithm used in the Amazon SageMaker LDA algorithm consult the following papers:
- David Blei, Andrew Ng, and Michael Jordan. Latent Dirichlet Allocation. Journal of Machine Learning Research, 3(Jan):993-1022, 2003.
- Animashree Anandkumar, Rong Ge, Daniel Hsu, Sham Kakade, and Matus Talgersy. Tensor Decompositions for Learning Latent Variable Models. Jounrla of Machine Learning Research, 15:2773-2832, 2014.
- Tamara Kolda and Brett Bader. Tensor Decompositions and Applications. SIAM REview, 51(3):455-500, 2009.