Eigen vectors helps in identifying the directions of highest variance in the data, which are then used to construct principal components. These principal components allows you to represent the data in a lower-dimensional while saving as much meaningful information as possible.
MACHINE LEARNING
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Fit Method: Computing Eigenvalues, Eigenvectors, and Dimensionality Reduction
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Now define the "fit" method that takes in that data and calculates the mean, normalizes the data, computes the covariance matrix, eigenvalues, and eigenvectors. Then the Eigenvectors are sorted based on eigenvalues. You may ask how, eigen vectors does dimensionality reduction?
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PCA Class Implementation: Initializing Components and Eigenvectors
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First Import numpy and define a class named "PCA" to encapsulate the operations. In the __init__ constructor let's initialize the number of components to reduce to, which is n_components, and similarly create placeholders for mean and eigenvectors.
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Principal Component Analysis PCA Explained and Implemented from Scratch
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Princiapal Component Analysis (PCA) clearly explained and implemented from scratch in Python:
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LIGER: Novel Approach Combining Model Embeddings With Weak Supervision
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Mayee Chen from Stanford shared fascinating insights on LIGER, a novel approach that combines model embeddings with weak supervision. LIGER's relevance and impact continue to resonate https://
youtube.com/watch?v=SfN8oe
G-M6E
… #stanford #ligermodel #machinelearning #NLP #AI -
Statistical Thermodynamics of Generative Diffusion Models
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The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability Ambrogioni et al.: https://
arxiv.org/abs/2310.17467 #ArtificialIntelligence #DeepLearning #MachineLearning -
10 AI-Powered Business Solutions by Abacus AI for Enterprise Growth
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Here are 10 #AI-powered business solutions from @AbacusAI to help your company get to the next level, using the best #MLOps and #LLMOps platform in the market. Start now: https://
abacus.ai
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#GenerativeAI #LLMs #MachineLearning #DataScience #DeepLearning #GenAI #ML -
Georgia Tech Faculty Honored on CIOS 2023 Fall Roll
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I am thrilled to be among faculty members at Georgia Tech who made the CIOS 2023 Fall Honor Roll.
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MM1: Methods and Insights from Multimodal LLM Pre-training
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training McKinzie et al.: https://
arxiv.org/abs/2403.09611 #ArtificialIntelligence #DeepLearning #MachineLearning -
Moore’s Law for Language Models: Performance and Speed Trade-offs
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Trying to think about what a Moore's Law for Language Models would look like. the problem i'm running into is that there are two separate axes to improve upon: model ability for a given model size (perplexity) and inference speed (tokens per second) Anyway, we can all agree