Essentials of Python for Artificial Intelligence and Machine Learning / by Pramod Gupta, Anupam Bagchi.

Format:

Book

Author/Creator:

Gupta, Pramod.

Contributor:

Bagchi, Anupam.

Series:

Synthesis Lectures on Engineering, Science, and Technology, 2690-0327

Language:

English

Subjects (All):

Electronic circuits.

Machine learning.

Signal processing.

Electronic Circuits and Systems.

Machine Learning.

Signal, Speech and Image Processing.

Local Subjects:

Electronic Circuits and Systems.

Machine Learning.

Signal, Speech and Image Processing.

Physical Description:

1 online resource (524 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python’s advanced module features and apply them in probability, statistical testing, signal processing, financial forecasting, and various other applications. This includes mathematical operations with array data structures, Data Manipulation, Data Cleaning, machine learning, Data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits using the core scientific packages NumPy, Pandas, SciPy, Sklearn/Scikit learn and Matplotlib. Readers will gain a deep understanding with problem-solving experience on these powerful platforms when dealing with engineering and scientific problems related to Machine Learning and Artificial Intelligence. Several examples of real problems using these techniques are provided along with examples. The authors also focus on the best practices in the industry on using Python for AI and ML. Deployment on a cloud infrastructure is described in detail (with code) to emphasize real scenarios. Includes several real examples of how to write and deploy code, including on a cloud infrastructure Provides single-source on Python for machine learning and artificial intelligence, from basics to real implementation Includes sufficient coverage of Python libraries, frameworks, and tools to develop complex data science applications.

Contents:

Introduction

Statistical Methods and Models

Python Language Basics

Introduction to Numpy

Introduction to Pandas

Data Manipulation With Pandas

Data Visualization With Python

Machine Learning

Data Pipelines Using Python

Mlops: Machine Learning Operations.

ISBN:

9783031437250

303143725X

OCLC:

1422229312