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[패스트캠퍼스] AI 기술을 활용한 의료 데이터 분석과 바이오 진단 학습후기카테고리 없음 2025. 5. 14. 19:25
전반적으로 강의에서 소개되는 기술들은 현재 서비스나 제품에서 활용되는 최신 기술들이라기보다는 몇 년전까지 사용되던 기술들이라는 인상을 받았다. 다만, 최신 기술들도 결국에는 해당 기술들의 아이디어나 한계점을 개선하기 위한 방법들이기 결국 모두 알아야하는 내용들이라고 판단되었기 때문에 관심을 가지고 수강하게 되었다. 해당 강의에서 절반은 MLP, CNN, RNN, Transformer, GAN 등 주요 Deep Learning 기초들을 다루고 있고 나머지 절반은 의료에서 주로 사용되는 데이터처리, 학습방법, 평가방법, 응용 분야 등을 다루고 있다. 워낙 다루는 범위가 넓다보니 하나의 기술이나 논문에 대해서 짧게는 몇 십초에서 길게는 몇 분정도의 분량을 가지고 있다. 하지만 해당 기술들이나 논문에 대해서 너..
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Accept-Reject SamplingStats 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 FactorizationMLAI/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 FilteringMLAI/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 SoftmaxMLAI/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 PersonalizeMLAI/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 FilteringMLAI/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 AnalysisMLAI/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..