Split Your Dataset for Training, Validation and Testing: Using split-foldersWhen training machine learning models, especially for image classification, it鈥檚 important to split your dataset into training, validation, and test sets. Instead of writing manual scripts to shuffle and copy files, you can use a simple yet powerful ...Oct 6, 2025 路 2 min readnischalbaidar.hashnode.dev
Comparing ML Classifiers for Sonar Data: Which One Works Best?Introduction: In the world of machine learning, selecting the right model for your dataset can often feel like a game of trial and error. For this blog, I鈥檓 diving into the Sonar rock vs mine classification problem, where I tested various machine lea...Apr 19, 2025 路 3 min readnischalbaidar.hashnode.dev
馃 Prompt Engineering: The Art of Talking to AIWhat is Prompt Engineering? In simple terms, prompt engineering is the art of crafting effective inputs鈥攐r prompts鈥攖o guide an AI model toward producing useful and relevant outputs. Unlike traditional programming, where you write code to give instruc...Apr 14, 2025 路 4 min readnischalbaidar.hashnode.dev
Day 16 - Univariate Exploratory Data Analysis (EDA) in PythonExploratory Data Analysis (EDA) is a critical step in any data analysis or data science project. It helps us understand the underlying patterns, spot anomalies, and check assumptions about the data before we dive deeper into modeling. What is Univari...Oct 20, 2024 路 1 min readnischalbaidar.hashnode.dev
Day 15 - Understanding Your Data by Asking QuestionsWhen working with data, the first step to making sense of it is to ask the right questions. These questions guide your exploration and help you gather insights before diving into any analysis or modeling. How Big is the Data? Check the number of ro...Oct 19, 2024 路 2 min readnischalbaidar.hashnode.dev