Quick pocket size Revision Guide for Data Science field-Part1

By: Nayak, Ravindra Kumar

Part 1: Data Science Libraries and Techniques

Pandas: Manages data with DataFrames and Series; supports loading, cleaning, manipulating, and exporting data.
NumPy: Performs numerical operations and linear algebra with arrays.
Scikit-learn: Facilitates machine learning with model building, preprocessing, and evaluation.
Seaborn & Matplotlib: Visualize data; Seaborn for statistical plots, Matplotlib for basic and custom charts.
Plotly & D3.js: Create interactive and advanced web-based visualizations.

• Format: Paperback
• Language: English
• ISBN: B0DBQBSBK1
• ISBN13: 9798334583139
• Release Date: July 2024
• Publisher: Independently Published
• Length: 76 Pages
• Weight: 0.44 lbs.
• Dimensions: 0.2" x 8.5" x 11.0"