When working with real-world datasets, we often have: Numerical features (e.g., Age, Salary) Categorical features (e.g., Gender, Country) To improve model performance, we need to:✔ Standardize numerical features (for algorithms sensitive to scale...
1. Introduction In software engineering, the term “boilerplate” refers to repetitive or standardized code that appears in many projects with only minor changes. Although it might seem like a “copy-paste” approach, boilerplate is crucial for quick pro...
When working on Machine Learning projects, we often need to adjust the data to make algorithms run faster and more efficiently. This adjustment involves methods like Normalization and Standardization. Normalization $$X normalized = X-Xmin/Xmax- Xmin$...
Are you looking for a way to monetize your talents and achieve financial freedom? Look no further than productized services, a powerful business model that's transforming how professionals offer their skills to the market. What Are Productized Servic...
Before feeding raw data into a machine learning model, we need to process and transform it to create features that the model can understand and learn from. This process is known as feature engineering. It involves several steps, each aimed at enhanci...
We'll use a school grading system across different subjects as our analogy. import numpy as np import pandas as pd from sklearn.preprocessing import StandardScaler # Example data: test scores in different subjects data = { 'math_score': [65, 70,...
Technology standardization is the reason that our web experience is so seamless, we can switch from diverse platforms and still feel at ease. From the seamless rendering of web pages to the interoperability of mobile apps, adherence to standardized p...
In this part of the series, I'll focus on Filtering and Versioning optimization in EDA. Some From The Past In the previous parts, we focused on Event Envelope Promises documenting Validation Filtering Event Driven Design introduces some comple...
The cyber industry's rapid growth has revolutionized how we live and work, ushering in a new era of connectivity and digital innovation. However, despite the industry's advancements, a widely adopted API (Application Programming Interface) protocol s...
Feature scaling is a data preprocessing technique that involves transforming the value of features or variables in a dataset to a similar scale. Feature scaling can vary your results a lot while using certain algorithms and have minimal or no effect ...
