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Home > Computing and Information Technology > Computer programming / software engineering > Programming and scripting languages: general > Learn Artificial Intelligence From Scratch: A Beginner's Guide To Understanding & Building AI Systems: A Comprehensive Introduction To The Field Of AI, Covering Fundamental Concepts & Key Tech
Learn Artificial Intelligence From Scratch: A Beginner's Guide To Understanding & Building AI Systems: A Comprehensive Introduction To The Field Of AI, Covering Fundamental Concepts & Key Tech

Learn Artificial Intelligence From Scratch: A Beginner's Guide To Understanding & Building AI Systems: A Comprehensive Introduction To The Field Of AI, Covering Fundamental Concepts & Key Tech


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About the Book

You'll Learn: Understand the Core Concepts of AI: Grasp the fundamental definitions of Artificial Intelligence, Machine Learning, and Deep Learning, and understand the historical context and different types of AI (ANI, AGI, ASI). Set Up Your AI Development Environment: Learn to install and configure essential tools like Python, Anaconda, and key libraries such as NumPy, Pandas, and Matplotlib to create your personal "AI workbench" for hands-on practice. Master the Role of Data in AI: Discover why data is the foundation of AI systems, learn to handle different data types, and gain practical skills in loading, exploring, and visualizing datasets using the Pandas library. Distinguish Different AI Learning Paradigms: Differentiate between rule-based systems and machine learning, and gain a clear understanding of the three core machine learning paradigms: supervised, unsupervised, and reinforcement learning. Build and Evaluate Predictive Models: Implement and train classic supervised learning models like Linear Regression for predicting numbers and Logistic Regression and Decision Trees for classification tasks using the Scikit-learn library. Discover Patterns in Unlabeled Data: Learn the principles of unsupervised learning and apply the K-Means clustering algorithm to group similar data points and find hidden structures within datasets. Assess and Improve Model Performance: Go beyond basic accuracy by learning about crucial evaluation metrics like the Confusion Matrix, Precision, Recall, and F1-Score. You'll also learn techniques like cross-validation and basic hyperparameter tuning to build more robust models. Build and Train Simple Neural Networks: Gain an intuitive understanding of how neural networks mimic the brain, learning about perceptrons, layers, and neurons. You'll then use a powerful library like Keras to build and train your first neural network classifier. Explore Key AI Applications: Get a foundational overview of specialized AI fields like Computer Vision (enabling machines to "see") and Natural Language Processing (enabling machines to understand language), including a brief introduction to Convolutional Neural Networks (CNNs). Understand the Ethical Implications of AI: Critically examine important considerations like algorithmic bias, privacy, and fairness in AI systems, and explore the future societal impact and career opportunities in the field.


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Product Details
  • ISBN-13: 9798290047089
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 279 mm
  • No of Pages: 154
  • Returnable: N
  • Sub Title: A Beginner's Guide To Understanding & Building AI Systems: A Comprehensive Introduction To The Field Of AI, Covering Fundamental Concepts & Key Tech
  • Width: 216 mm
  • ISBN-10: 8290047088
  • Publisher Date: 28 Jun 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 8 mm
  • Weight: 375 gr


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Learn Artificial Intelligence From Scratch: A Beginner's Guide To Understanding & Building AI Systems: A Comprehensive Introduction To The Field Of AI, Covering Fundamental Concepts & Key Tech
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