TensorFlow Developer Certificate Guide. Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam - Helion
Tytuł oryginału: TensorFlow Developer Certificate Guide. Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam
ISBN: 9781803249209
stron: 350, Format: ebook
Data wydania: 2023-09-29
Księgarnia: Helion
Cena książki: 139,00 zł
The TensorFlow Developer Certificate Guide is an indispensable resource for machine learning enthusiasts and data professionals seeking to master TensorFlow and validate their skills by earning the certification. This practical guide equips you with the skills and knowledge necessary to build robust deep learning models that effectively tackle real-world challenges across diverse industries.
You’ll embark on a journey of skill acquisition through easy-to-follow, step-by-step explanations and practical examples, mastering the craft of building sophisticated models using TensorFlow 2.x and overcoming common hurdles such as overfitting and data augmentation. With this book, you’ll discover a wide range of practical applications, including computer vision, natural language processing, and time series prediction.
To prepare you for the TensorFlow Developer Certificate exam, it offers comprehensive coverage of exam topics, including image classification, natural language processing (NLP), and time series analysis. With the TensorFlow certification, you’ll be primed to tackle a broad spectrum of business problems and advance your career in the exciting field of machine learning. Whether you are a novice or an experienced developer, this guide will propel you to achieve your aspirations and become a highly skilled TensorFlow professional.
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Spis treści
TensorFlow Developer Certificate Guide. Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam eBook -- spis treści
- 1. Introduction to Machine Learning
- 2. Introduction to Tensorflow
- 3. Linear Regression with Tensorflow
- 4. Classification with Tensorflow
- 5. Image Classification with Neural Networks
- 6. Improving the model
- 7. Image Classification with Convolution Neural Networks
- 8. Handling Overfitting
- 9. Transfer Learning
- 10. Introduction to Natural Language Processing
- 11. Natural Language Processing with Tensorflow
- 12. Introduction to Time Series, Sequence and Prediction
- 13. Time Series, Sequence and Prediction with Tensorflow