CodeStips

Data Analysis

Implementing K-Means in Python

Machine Learning & AI

Learn to build K-Means clustering from scratch in Python without machine learning libraries. Step-by-step implementation guide for beginners and enthusiasts.

Installing Jupyter Notebook on macOS

Installation & Setup

Learn to install Jupyter Notebook on macOS for data analysis and prototyping, with tips on managing Python environments and initial setup.

Introduction to Seaborn for Visualization

Data Analysis & Visualization

Seaborn simplifies data visualization in Python by offering a high-level interface built on Matplotlib. It helps create attractive and informative statistical graphics with less code and more polish.

Linear Regression Explained

Machine Learning & AI

Linear regression is a simple machine learning tool that finds a best-fit straight line to make predictions based on observed data patterns.

Memory Management in DataFrames

Data Analysis & Visualization

Optimize DataFrame memory usage to prevent slow performance and crashes when handling large datasets. Learn essential techniques for efficient data analysis.

NumPy Array Operations

Libraries & Frameworks

Learn how NumPy's array operations enable efficient numerical computations, offering high performance for handling large datasets and matrices in Python.

Overfitting and Underfitting in ML

Machine Learning & AI

Overfitting occurs when a model learns training data too well, including noise, making it perform poorly on new data. Underfitting happens when a model fails to capture patterns in the data, resulting in poor performance overall.

Plotly: Interactive Visualizations

Libraries & Frameworks

Plotly is a Python library for creating interactive, web-based charts and visualizations, ideal for dynamic data exploration and storytelling.

Plotly Scatter Plots

Data Analysis & Visualization

Learn how to create interactive scatter plots with Plotly to visualize relationships, clusters, trends, and distributions in your Python data.

Python Data Analysis Cheatsheet

Cheatsheets & Reference Guides

Master the essentials of Python data analysis with this guide to key libraries like pandas, NumPy, and Matplotlib. Learn workflows and functions for efficient data handling and visualization.