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February 13, 2024

3D Reconstructions from a Single Image Using Multi-View Diffusion Models

Reconstructing 3D Assets with an Image 3D Reconstructions from a Single Image can transform how we create digital models. Today, anyone can build detailed three-dimensional

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February 13, 2024

Hurst Exponent on a Rolling Basis in Python

Charting Market Rhythms: The Rolling Hurst Exponent in Python Ever tried catching the rhythm of the stock market? If you have, you’d know trends aren’t

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February 12, 2024

Assessing Future Stock Price Movements with Historical & Implied Volatility

Price Movement Estimation Using Historical and Implied Volatility 1. Introduction Forecasting financial markets is a sophisticated fusion of quantitative precision and global economic nuance. In this

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February 12, 2024

Interactive Stock Price Movement Probabilities with Python

Dynamic Price Movement Probability 1. Introduction When diving into the financial world, understanding stock price movements is a significant advantage. Here, we present an interactive

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February 12, 2024

Expected Stock Price Movement with Volatility Multipliers

Expected Stock Price Movement with Python Figure 1. Projected Stock Price Movement for ASML.AS over a 20-Day Horizon: Visualizing the Impact of Different Volatility Multipliers

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February 12, 2024

Analyzing Rolling Z-Score in Stock Trading with Python

Analyzing Z-Scores in Stock Trading Figure 1. Evolution of ASML.AS stock prices juxtaposed with rolling Z-Scores over 30, 60, and 90-day periods. Green and red

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February 7, 2024

Fine-Tuning Your Own Custom Stable Diffusion Model with just 4 Images

End-to-End Python Guide For Giving a Stable Diffusion Model Your Own Images for Training and Making Inferences from Text Stable Diffusion models have gained significant attention

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February 6, 2024

AI Face Restoration in Images with CodeFormer

Restoring, Colorizing and Inpainting AI Face Restoration technology enhances and recovers facial images from various states of degradation. This technology restores clear visuals from once-flawed

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