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- Title: Machine Learning with Python Tutorial
- Author(s): Bernd Klein
- Publisher: Python Course
- Paperback: N/A
- eBook: HTML and PDF (
- Language: English
- ISBN-10: N/A
- ISBN-13: N/A
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This practical guide provides helps to solve machine learning challenges you may encounter in your work. Go beyond theory and concepts by learning the nuts and bolts you need to construct working machine learning applications.
About the Authors- N/A
- Machine Learning
- Neural Networks and Deep Learning
- Python Programming
- Artificial Intelligence
- Data Science
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Deep Learning with Python, 2nd Edition (Francois Chollet)
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Deep Neural Networks and Data for Automated Driving
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Physics-Based Deep Learning (Nils Thuerey, et al.)
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Hyperparameter Tuning for Deep Learning: A Practical Guide
This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods.
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Deep Learning with Python, 2nd Edition (Francois Chollet)
This book introduces the field of deep learning using Python and the powerful Keras library. It offers insights for both novice and experienced machine learning practitioners, and builds your understanding through intuitive explanations and practical examples.
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Dive into Deep Learning (Aston Zhang, et al.)
This is an open source, interactive book provided in a unique form factor that integrates text, mathematics and code, now supports the TensorFlow, PyTorch, and Apache MXNet programming frameworks, drafted entirely through Jupyter notebooks.
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Deep Learning for Coders with Fastai and PyTorch
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Deep Learning with PyTorch (Eli Stevens, et al.)
This book teaches you to create deep learning and neural network systems with PyTorch. It gets you to work right away building a tumor image classifier from scratch. You'll learn best practices for the entire deep learning pipeline, tackling advanced projects.
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