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github.com | ||
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www.nicktasios.nl
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| | | | | In the Latent Diffusion Series of blog posts, I'm going through all components needed to train a latent diffusion model to generate random digits from the MNIST dataset. In this first post, we will tr | |
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kavita-ganesan.com
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| | | | | This article examines the parts that make up neural networks and deep neural networks, as well as the fundamental different types of models (e.g. regression), their constituent parts (and how they contribute to model accuracy), and which tasks they are designed to learn. | |
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www.ethanrosenthal.com
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| | | | | How would you build a machine learning algorithm to solve the following types of problems? Predict which medal athletes will win in the olympics. Predict how a shoe will fit a foot (too small, perfect, too big). Predict how many stars a critic will rate a movie. If you reach into your typical toolkit, you'll probably either reach for regression or multiclass classification. For regression, maybe you treat the number of stars (1-5) in the movie critic question as your target, and you train a model using m... | |
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blog.adnansiddiqi.me
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| | | What Is Synthetic Data? Synthetic data is machine-generated data based on real-world data. It requires building a machine learning (ML) model to capture the patterns in the original, real data before generating new synthetic data based on these patterns. The generated data accurately represents the original data's statistical distributions, patterns, and properties. Synthetic data is | ||
