Demyank's Tlog Demyank's Tlog

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• Accept-Reject Sampling

  Stats 2022. 7. 14. 13:43

  Sample and Sampling Sample A sample is an outcome of a random experiment. When we sample a random variable, we obtain one specific value out of the set of its possible values. That particular value is called a sample. The possible values and the likelihood of each are determined by the random variable's probability distribution. Sampling Mathematically performing sampling is the same as performi..

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• Matrix Factorization

  MLAI/RecommendSystem 2022. 7. 12. 18:58

  Introduction Split the matrix into the product of 2 other matrices We call it R hat because it only approximates R - it is our model of R We would like W and U to be very skinny $W(N \times K)$ - users matrix, $U(M \times K)$ - movie matrix K somewhere from 10-50 The scale of matrix R, W, and U Key: $W$ and $U$ should be much smaller than $R$ $R$ is $N \times M$ Generally, we can't store $R$ in ..

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• Item-Item Collaborative Filtering

  MLAI/RecommendSystem 2022. 7. 12. 14:49

  Intuition The correlation between the column vectors is high If you like Power Rangers, you'll also like Transformers because users give them similar ratings Power Rangers Transformers Ninja Turtles User 1 4.5 5 4 User 2 5 5 4.5 User 3 1 2 0.5 User 4 2 2 0.5 User-User Collaborative Filtering For user-user CF, I want to find "users like me" The movies that those users have seen, that I haven't se..

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• Sigmoid and Softmax

  MLAI/DeepLearning 2022. 7. 7. 18:32

  1. Softmax Softmax function calculates the probability distribution of the event over k different events. This function will calculate the probabilities of each target class over all possible target classes. Equation $$P(y=j | x) = \frac{e^{x_j}}{\sum_{k=1}^K e^{x_k}}$$ Plot x = np.arange(-2.0, 6.0, 0.1) input = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)]) Characteristic It normalizes ..

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• AWS Personalize

  MLAI/RecommendSystem 2022. 7. 7. 17:59

  Built-in Recipe (Model) Sims Based on collaborative filtering. SIMS identifies the co-occurrence of the item in user histories in your Interaction dataset to recommend similar items. For example, with SIMS Amazon Personalize could recommend coffee shop items customers frequently bought together or movies that different users also watched. Recommended for improved item searchability and faster pe..

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• User-User Collaborative Filtering

  MLAI/RecommendSystem 2022. 7. 7. 17:41

  Batman X-Men Star Wars The Notebook Bridget Jones' Diary Alice 5 4.5 5 2 1 Bob 4.5 4 2 2 Carol 2 3 1 5 5 Intuitively, we see that Bob’s ratings are similar to Alice’s, thus he is likely to also like Star Wars. In math-speak, Alice’s and Bob’s ratings are highly correlated. Average Rating Limitations It treats everyone’s rating of the movie. equally. Bob’s s(i, j) equally depends on Alice’s ratin..

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• Association Analysis

  MLAI/RecommendSystem 2022. 7. 7. 17:31

  Definition As a role-based model, it is an algorithm that finds out how an item relates to another item. This association exists in two forms. How often are they purchased together? (Frequent) If someone bought item A, will he also buy item B? It is also expressed as a shopping Market basket analysis because it is similar to looking at which products are contained in one shopping basket. Ex) Fam..

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• AWS MSK

  Data Engineering 2022. 7. 1. 20:05

  Overview Alternative to Kinesis (Kafka vs Kinesis next lecture) Fully managed Apache Kafka on AWS Allow you to create, update, delete clusters MSK create & manages Kafka brokers nodes & Zookeeper nodes for you Deploy the MSK cluster in your VPC, multi-AZ (up to 3 for HA) Automatic recovery from common Apache Kafka failures Data is stored on EBS volumes You can build producers and consumers for y..

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