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As a machine learning practitioner, I have found Kaiming initialization to be an invaluable tool for training deep neural networks effectively. In this article, I will delve into the key aspects of Kaiming initialization and how it can help unlock the full potential of your neural network models. Understanding the Vanishing and Exploding Gradient Problem […]

Triangular arbitrage is a time-sensitive trading strategy that capitalizes on discrepancies between the exchange rates of three currency pairs. The essence of this strategy lies in converting one currency into another, then another, and back into the original currency, exploiting slight inefficiencies in the pricing to secure a profit. Given that currency markets are incredibly

The Anderson-Darling test is a statistical test used to determine if a sample comes from a population with a specific distribution. It is particularly useful for assessing whether a dataset follows a normal distribution. Key Points Advantages of the Anderson-Darling Test Performing the Anderson-Darling Test in Python You can perform the Anderson-Darling test in Python

The Shapiro-Wilk test is a widely used statistical test for assessing the normality of a dataset. It helps determine whether a sample comes from a normally distributed population. This test is particularly useful in fields such as data science, finance, and biology, where the assumption of normality is often critical for further statistical analysis. Understanding

Here’s a project idea that you can publish on your website to showcase your skills as a Quantitative Analyst: Project: “Stock Market Analysis and Prediction using Machine Learning” Objective: To analyze the historical stock prices of a selected company and build a predictive model to forecast future stock prices using machine learning techniques. Dataset: Choose