Mastering Machine Learning: From Basics to Advanced

Chapter 1: Introduction.- Chapter 2: Python Programming Using Google Cloud (COLAB).- Chapter 3: Introduction to Colab: Google Cloud Development Environment.- Chapter 4: Getting started with python.-Chapter 5: Conditions.- Chapter 6: Loops.- Chapter 7: Functions.- Chapter 8: Arrays.- Chapter 9: NumPy.-Chapter 10: PANDAS.- Chapter 11: Data Visualization using Matplotlib.- Chapter 12: Dependent Vs. Independent Variables.- Chapter 13: Types of Data.- Chapter 14: Population Vs. Sample.- Chapter 15: Hypothesis Testing.- Chapter 16: Machine Learning Concepts .- Chapter 17: Measuring Accuracy in Algorithms.- Chapter 18: Understanding Regression Concepts.- Chapter 19: Simple Linear Regression (Programming).- Chapter 20: Advanced Data Visualization for Regression.- Chapter 21: Multiple Linear Regression (Programming).- Chapter 22: Gradient Descent.- Chapter 23: Logistic Regression (Programming).- Chapter 24: Unsupervised Learning – Concepts & Programming.- Chapter 25: Exploratory Data Analysis.

• Erscheinungsdatum: 18.04.2025
• Autor/Autorin: Govindakumar Madhavan
• Reihe: Transactions on Computer Systems and Networks
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 11.2 MB
• Verlag: SPRINGER
• Sprache: Englisch
• ISBN: 9789819799145
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.