Category: Free Reading

Introduction Exploratory Data Analysis (EDA) is an essential step in the data analysis process. It involves examining and visualizing a dataset to understand its main characteristics, find patterns, detect anomalies, and check assumptions using summary statistics and graphical representations. EDA is often the first step performed after data collection and cleaning, and it helps analysts…

Introduction Feature engineering is an essential step in the data analysis and machine learning process. It involves creating new input features from existing raw data to improve the performance of predictive models. This step is critical because well-crafted features can lead to more accurate and efficient models. Why is Feature Engineering Important? Key Steps in…

What is Data Analysis? Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making. It is a crucial process in various fields, including business, science, social sciences, and technology, as it helps individuals and organizations understand trends, patterns, and insights hidden…

Introduction Machine learning (ML) is a field of artificial intelligence (AI) that allows systems to learn from data and improve from experience without being explicitly programmed. Among the various types of ML, supervised learning is one of the most commonly used. In this guide, we will break down what supervised learning is, focusing on regression…

Introduction Unsupervised learning is a subset of machine learning where the algorithm is trained on data without any labeled outputs. Unlike supervised learning, where the algorithm learns from input-output pairs to make predictions or classifications, unsupervised learning works by finding hidden patterns or intrinsic structures in the input data. Here, we will discuss two main…

Introduction Mean reversion is a popular algorithmic trading strategy used by traders and quantitative analysts. This strategy is based on the statistical concept that asset prices and returns eventually revert to their long-term average or mean. Let’s break down what this means, how it works, and how it’s applied in the financial markets. What is…

Introduction Momentum trading is a popular strategy in the realm of algorithmic trading, where traders seek to capitalize on the continuing trends of asset prices. By employing computer algorithms, this strategy can be automated to analyze massive datasets, make fast decisions, and execute trades efficiently. Here’s an in-depth explanation: What is Momentum Trading? Momentum trading…

Introduction Pairs trading is a market-neutral trading strategy used in algorithmic trading, and it’s based on the concept of trading two related stocks simultaneously to capitalize on their price discrepancies. Here’s a detailed breakdown of what pairs trading entails, how it works, and why it’s popular among algorithmic traders: Understanding Pairs Trading Pairs trading involves…