#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Distributed machine learning examples
1. DISTRIBUTED MACHINE LEARNING EXAMPLES
STANLEY WANG
SOLUTION ARCHITECT, TECH LEAD
@SWANG68
http://www.linkedin.com/in/stanley-wang-a2b143b
2. Topic Modeling
• Topical categorization of blogs, documents or other objects that can be tagged with
text, improves the experience for end users;
• Discover Sets of
Topics from Large
Unstructured
Collections of
documents;
• Annotate
documents with
topic;
• Utilize Annotation
to Index, Search
and Classify on
documents;
3. The Intuitions behind LDA
• Latent Dirichlet Allocation (LDA) is an unsupervised, probabilistic, text
clustering algorithm. LDA defines a generative model that can be used
to model how documents are generated given a set of topics and the
words in the topics;
4. Graphical Model for LDA
• Topic-based text
classification;
• Topic modeling can be seen as
a pre-processing step before
applying supervised learning
methods, such as
Collaborative Filtering;
• Finding patterns in genetic
data, images, and social
networks;
5. Real Inference with LDA
• A 100-topic LDA model was fitted to 17,000 articles from the Science journal;
• At right are the top 15 most frequent words from the most frequent topics;
• At left are the inferred topic proportions for the example article from previous slide;
8. What is Community Intuition?
In social world, community is a collection of users that are more closely
related to each other than the rest of the network. The relation between users
can be amount of interaction, similar interest, geographical factors etc.
9. Why Detect Social Communities?
• Behavior Analysis
• Location-based Interaction Analysis
• Recommender Systems Development
• Link Prediction
• Customer Interaction and Analysis
• Media & Content Analysis
• Security
• Social Studies