Utvidet returrett til 31. januar 2025

Essentials of Python for Artificial Intelligence and Machine Learning

Om Essentials of Python for Artificial Intelligence and Machine Learning

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.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9783031437243
  • Bindende:
  • Hardback
  • Sider:
  • 509
  • Utgitt:
  • 15. februar 2024
  • Utgave:
  • 12024
  • Dimensjoner:
  • 174x249x116 mm.
  • Vekt:
  • 1010 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 19. desember 2024

Beskrivelse av Essentials of Python for Artificial Intelligence and Machine Learning

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.

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