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Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and Keras English Edition Paperback October 19, 2021
Learn AI with Python is a practical guide that covers the essential aspects of AI and provides hands-on experience with various machine learning and deep learning algorithms, logic programming, neural networks, and natural language processing through real-world examples and fully functional Python implementation.
Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and Keras English Edition Paperback October 19, 2021
Item #: 46978796

Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and

Item #: 46978796

ZAR 778

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Learn AI with Python is a practical guide that covers the essential aspects of AI and provides hands-on experience with various machine learning and deep learning algorithms, logic programming, neural networks, and natural language processing through real-world examples and fully functional Python implementation.
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What Stands Out

Comprehensive Learning
This book offers an in-depth exploration of both machine learning and deep learning, providing readers with the knowledge required to build intelligent AI systems effectively.
Practical Tools
Utilizes popular libraries like Scikit-Learn, NLTK, NeuroLab, and Keras, ensuring readers gain hands-on experience with industry-standard tools to tackle real-world AI challenges.
Beginner-Friendly
Designed for learners at all levels, this guide simplifies complex concepts, making machine learning accessible and engaging for newcomers to the field.

Product Details

Explore Machine Learning and Deep Learning techniques with Python. Build Smart AI Systems using Scikit-Learn, NLTK, NeuroLab, and Keras. English Edition Paperback available at Ubuy South Africa.
  • Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems
  • Covers practical aspects of Machine Learning and Deep Learning concepts
  • Includes graphical illustrations of Natural Language Processing using NLTK
  • Covers deep learning models such as R-CNN and YOLO for object recognition
  • Teaches how to build an image classifier using Convolutional Neural Networks (CNNs)
  • Suitable for beginners and intermediate Machine Learning practitioners
Item Weight1.1 lbs (500 grams)

Who Should Buy?

Suitable For
  • Beginner Programmers

    Individuals with basic Python skills seeking to understand AI fundamentals and machine learning techniques step-by-step.

  • Data Science Students

    Students looking to enhance their knowledge in AI and machine learning with practical examples and Python libraries.

  • AI Enthusiasts

    Technology enthusiasts eager to grasp the principles of AI development and explore real-world applications.

Not Suitable For
  • Advanced Practitioners

    Experienced developers or data scientists may find the content too basic or lacking in advanced topics and techniques.

  • Non-Technical Users

    Individuals without programming experience may struggle with the technical concepts and require more foundational knowledge.

  • Quick Learners

    Users needing rapid skill acquisition may find the gradual approach unsuitable for fast-paced learning environments.

Product Description

Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and Keras English Edition Paperback October 19, 2021

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Intelligence & Semantics Editorial Review

The book appears to be a comprehensive guide for those interested in Machine Learning and Data Science. It covers basic to advanced topics with well-thought-out explanations and well-chosen code examples. The author has done a good job in justifying the inclusion of some intricate topics that are not readily available on the internet. It has been recommended as a must-read for every ML and Data Science aspirant. The print quality of the book is excellent.

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Pros

  • Comprehensive guide for beginners and those with some knowledge of ML
  • Covers basic to advanced topics
  • Excellent print quality
  • Well-thought-out explanations
  • Well-chosen code examples

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