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Practical AI for healthcare professionals machine learning with Numpy, Scikit-learn, and TensorFlow

What You'll Learn Distinguish between problems that currently can and cannot be solved with AI Master programming concepts not familiar to physicians, such as libraries, coding, and creating and training ML models Perform dataset analysis with decision trees, SVMs, and neural networks. Who This...

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Bibliographic Details
Main Author: Suri, Abhinav
Format: eBook
Language:English
Published: [United States] Apress 2022
Edition:1st edition
Subjects:
Artificial Intelligence / Medical Applications / Fast
Intelligence Artificielle / Applications En Médecine
Machine Learning / Http://id.loc.gov/authorities/subjects/sh85079324
Artificial Intelligence / Medical Applications / Http://id.loc.gov/authorities/subjects/sh88003000
Machine Learning / Fast
Apprentissage Automatique
Machine Learning
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Chapter 1: Introduction to AI and its Use Cases- Chapter 2: Computational Thinking
  • Chapter 3: Overview of Programming
  • Chapter 4: A Brief Tour of Machine Learning Algorithms. -Chapter 5: Project #1 Neural Networks & Heart Disease
  • Chapter 6: Project #2 CNNs & Brain Tumor Detection
  • Chapter 7: The Future of Healthcare and AI.

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