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Understanding Deep Learning: Building Machine Learning Systems with PyTorch and TensorFlow: From Neural Networks (CNN, DNN, GNN, RNN, ANN, LSTM, GAN) to Natural Language Processing (NLP)
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0.93 kg
0.93 kg
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Amazon
Amazon
Sobre este producto
- Foundations of Machine Learning and Deep LearningDiscover why machines learn the way they do and understand the algorithms that power modern machine learning models. Explore the evolution of AI, from basic network structures to sophisticated LLMs and RAG (retrieval-augmented generation) techniques.
- Practical Model Building with PyTorch and TensorFlowGet hands-on experience with Python programming, PyTorch, and TensorFlow—the most powerful tools in machine learning system design. Learn to build and optimize models that solve real-world problems, from NLP (Natural Language Processing) with Transformers to generative deep learning for image synthesis.
- Advanced Techniques for Model Optimization and System DesignMaster the art of hyperparameter tuning, data preprocessing, and system design for deep learning. This book also introduces GitHub and version control for efficient model management, essential for any data-driven project.
- Real-World ApplicationsWhether you’re interested in algorithmic trading, hands-on machine learning with scikit-learn, Keras, and TensorFlow, or understanding deep learning for natural language processing, this book covers it all. See how deep learning with PyTorch and machine learning with Python apply across fields, from data science to cutting-edge generative AI.
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