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Deep Learning Foundations Powering AI with Neural Networks: Master deep learning for image recognition and NLP
| AUTHOR | Myles, Isandro |
| PUBLISHER | Independently Published (09/09/2025) |
| PRODUCT TYPE | Paperback (Paperback) |
Unlock the power of neural networks and deep learning for AI-driven solutions.
In Deep Learning Foundations, you'll learn how to build and deploy deep learning models that power applications in image recognition, natural language processing (NLP), and more. Whether you're a beginner or looking to deepen your knowledge, this book will guide you through the fundamentals of deep learning and help you apply them to real-world AI challenges.
Inside, you'll discover how to:
Understand the basics of deep learning: learn about neural networks, activation functions, loss functions, and backpropagation.
Implement feedforward networks and convolutional neural networks (CNNs) for tasks like image classification and object detection.
Dive into recurrent neural networks (RNNs) and LSTMs for sequence data like time series and text.
Master transfer learning and leverage pre-trained models for faster, more efficient model development.
Develop NLP models using Word2Vec, BERT, and GPT for sentiment analysis, text generation, and language translation.
Use TensorFlow and Keras for building, training, and deploying deep learning models.
Apply regularization techniques like dropout, batch normalization, and early stopping to avoid overfitting.
Evaluate models using metrics like accuracy, precision, recall, F1 score, and more.
Fine-tune models with hyperparameter optimization, learning rate schedules, and grid/random search.
Learn how to work with real-world datasets and deploy models for production-ready AI solutions.
Packed with hands-on projects, step-by-step examples, and real-world applications, this book will provide you with the tools to build advanced AI models for industries like healthcare, finance, entertainment, and more.
Who This Book Is ForBeginners interested in learning deep learning and AI
Data scientists and machine learning engineers looking to apply deep learning to practical problems
Researchers and students exploring AI-driven solutions in image recognition and NLP
Developers seeking to implement deep learning models in real-world applications
Master the foundations of deep learning and build AI models that solve complex problems with cutting-edge techniques.
Unlock the power of neural networks and deep learning for AI-driven solutions.
In Deep Learning Foundations, you'll learn how to build and deploy deep learning models that power applications in image recognition, natural language processing (NLP), and more. Whether you're a beginner or looking to deepen your knowledge, this book will guide you through the fundamentals of deep learning and help you apply them to real-world AI challenges.
Inside, you'll discover how to:
Understand the basics of deep learning: learn about neural networks, activation functions, loss functions, and backpropagation.
Implement feedforward networks and convolutional neural networks (CNNs) for tasks like image classification and object detection.
Dive into recurrent neural networks (RNNs) and LSTMs for sequence data like time series and text.
Master transfer learning and leverage pre-trained models for faster, more efficient model development.
Develop NLP models using Word2Vec, BERT, and GPT for sentiment analysis, text generation, and language translation.
Use TensorFlow and Keras for building, training, and deploying deep learning models.
Apply regularization techniques like dropout, batch normalization, and early stopping to avoid overfitting.
Evaluate models using metrics like accuracy, precision, recall, F1 score, and more.
Fine-tune models with hyperparameter optimization, learning rate schedules, and grid/random search.
Learn how to work with real-world datasets and deploy models for production-ready AI solutions.
Packed with hands-on projects, step-by-step examples, and real-world applications, this book will provide you with the tools to build advanced AI models for industries like healthcare, finance, entertainment, and more.
Who This Book Is ForBeginners interested in learning deep learning and AI
Data scientists and machine learning engineers looking to apply deep learning to practical problems
Researchers and students exploring AI-driven solutions in image recognition and NLP
Developers seeking to implement deep learning models in real-world applications
Master the foundations of deep learning and build AI models that solve complex problems with cutting-edge techniques.