Mastering Machine Learning: From Basics to Advanced
Series: Transactions on Computer Systems and Networks;
- Publisher's listprice EUR 230.07
-
97 595 Ft (92 948 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
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97 595 Ft
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Product details:
- Edition number 2025
- Publisher Springer
- Date of Publication 4 June 2025
- Number of Volumes 1 pieces, Book + Online Course
- ISBN 9789819799138
- Binding Unidentified
- No. of pages250 pages
- Size 235x155 mm
- Language English
- Illustrations 89 Illustrations, black & white; 257 Illustrations, color 700
Categories
Short description:
This book covers all aspects of machine learning (ML) from concepts and math to ML programming. ML concepts and the math associated with ML are written from an application perspective, rather than from a theoretical perspective. The book presents concepts and algorithms precisely as they are used in real-world applications, ensuring a seamless and practical understanding with no gap between theory and practice.
In a distinctive approach, the book's content is complemented by video lectures whose details can be found inside the book. This innovative approach offers readers a multimedia learning experience, accommodating different learning preferences, and reinforcing the material through visual and auditory means. If you are new to Artificial Intelligence and Machine Learning, this could be the first book you read and the first video course you take.
MoreLong description:
This book covers all aspects of machine learning (ML) from concepts and math to ML programming. ML concepts and the math associated with ML are written from an application perspective, rather than from a theoretical perspective. The book presents concepts and algorithms precisely as they are used in real-world applications, ensuring a seamless and practical understanding with no gap between theory and practice.
In a distinctive approach, the book's content is complemented by video lectures whose details can be found inside the book. This innovative approach offers readers a multimedia learning experience, accommodating different learning preferences, and reinforcing the material through visual and auditory means. If you are new to Artificial Intelligence and Machine Learning, this could be the first book you read and the first video course you take.
MoreTable of Contents:
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.
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