Topic 1 Question 11
A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences, and trends to enhance the website for better service and smart recommendations. Which solution should the Specialist recommend?
Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.
A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database.
Collaborative filtering based on user interactions and correlations to identify patterns in the customer database.
Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database.
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answer should be C Collaborative filtering is for recommendation, LDA is for topic modeling
👍 18WWODIN2021/10/03In natural language processing, the latent Dirichlet allocation (LDA) is a generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar.
Amazon SageMaker Random Cut Forest (RCF) is an unsupervised algorithm for detecting anomalous data points within a data set
Neural network is used for image detection
Answer is C
👍 8syu31svc2021/10/25I'm thinking that it is A because:
- the input data that we have doesn't lend itself to collaborative filtering - it requires a set of items and a set of users who have reacted to some of the items, which is NOT what we have
- recommendation is just one thing that we want to do. What about trends?
- collaborative filtering isn't one of the pre-built algorithms (weak argument, admittedly)
👍 5sdsfsdsf2021/10/07
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