Treffer: PYTHON-BASED NEURAL NETWORKS FROM SCRATCH: A HANDS-ON DEEP LEARNING GUIDE

In this book, we embark on a comprehensive journey through thefascinating world of neural networks, exploring their practical uses,fundamental elements, implementation in Python, and advancedapplications in deep learning and natural language processing.Neural networks have revolutionized various fields, from computervision and natural language processing to recommender systems andchatbots. Their ability to learn complex patterns and makepredictions from data has made them indispensable tools in the ageof artificial intelligence.In the first part of this book, we provide an overview of neuralnetworks, discussing their practical applications in imagecomputing, natural language processing, and recommendationsystems. We delve into the essential elements of neural networks,including neurons, activation functions, layers, and backpropagation,laying the groundwork for understanding their architecture andoperation.Understanding the mathematics behind neural networks is crucial fortheir implementation and optimization. Therefore, we dedicate asection to the fundamentals of neural network mathematics, coveringlinear algebra, matrix operations, and derivatives, with practicalexamples and insights into optimization techniques.The heart of neural network training lies in gradient descent andbackpropagation algorithms. We provide a comprehensiveintroduction to these algorithms, discussing their principles,implementation, and optimization strategies for improving learningefficiency.Choosing the right activation functions, loss functions, andoptimization methods is crucial for the success of neural networkmodels. We discuss popular choices and their implications,equipping you with the knowledge to make informed decisions whendesigning and training neural networks.Implementing neural networks in Python is made accessible throughdetailed explanations and code examples. We guide you throughsetting up your Python environment, installing essential libraries likeTensorFlow and Keras, and building your first neural networkmodels from ...