# dragen1860/deep-learning-with-tensorflow-book

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13,237 stars · 4,032 forks · Jupyter Notebook

## Links

- GitHub: https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book
- Homepage: http://www.ai101edu.com
- awesome-repositories: https://awesome-repositories.com/repository/dragen1860-deep-learning-with-tensorflow-book.md

## Topics

`book` `deeplearning` `machinelearning` `opensource` `python` `pytorch` `tensorflow` `tensorflow2`

## Description

This project is an open source deep learning textbook and educational resource. It provides a structured curriculum of theory and practical examples designed for mastering the training of regression, classification, and generative models using the TensorFlow framework.

The repository functions as a machine learning code collection, utilizing interactive notebooks and source code to demonstrate neural network implementation and tensor operations. It covers the development of deep learning models and the study of reinforcement learning.

The material employs a case-study driven pedagogy, combining executable code with formatted text to demonstrate workflows. It utilizes the Keras high-level API and a layer-based architecture to translate deep learning theory into working implementations.

## Tags

### Education & Learning Resources

- [Deep Learning Fundamentals](https://awesome-repositories.com/f/education-learning-resources/deep-learning-curriculum/deep-learning-fundamentals.md) — Provides a comprehensive curriculum covering the fundamental principles and practical implementations of deep learning. ([source](https://github.com/dragen1860/deep-learning-with-tensorflow-book#readme))
- [Deep Learning Curriculum](https://awesome-repositories.com/f/education-learning-resources/deep-learning-curriculum.md) — Offers a structured learning path and curriculum for mastering the training of various deep learning models.
- [Deep Learning Education](https://awesome-repositories.com/f/education-learning-resources/deep-learning-education.md) — Serves as an educational resource for learning neural network theory and practice through structured curricula.
- [Educational Code Repositories](https://awesome-repositories.com/f/education-learning-resources/educational-code-repositories.md) — Functions as a source code collection specifically curated to accompany the educational textbook material.
- [Neural Network Implementations](https://awesome-repositories.com/f/education-learning-resources/educational-resources/reference-and-media/books-docs-reference/code-examples/reference-implementations/neural-network-implementations.md) — Provides code-based implementations of neural network architectures to translate mathematical theory into working software.
- [Technical Case Studies](https://awesome-repositories.com/f/education-learning-resources/technical-case-studies.md) — Provides a series of technical case studies and practical implementation examples to teach deep learning concepts.

### Artificial Intelligence & ML

- [Deep Learning Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/deep-learning-frameworks.md) — Provides an open source textbook and practical guide for implementing deep learning principles using TensorFlow.
- [High-Level Model APIs](https://awesome-repositories.com/f/artificial-intelligence-ml/high-level-model-apis.md) — Utilizes the Keras high-level API to simplify the construction and configuration of deep learning models.
- [TensorFlow Model Development](https://awesome-repositories.com/f/artificial-intelligence-ml/tensorflow-model-development.md) — Teaches how to build and train classification and regression models using the TensorFlow 2.0 framework.
- [Layered Architectures](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/frameworks/model-construction/neural-network-layers/convolution-layers/layered-architectures.md) — Structures neural networks as sequential stacks of operational layers to process data from input to prediction.
- [Training and Evaluation Pipelines](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-training-and-tuning/training-frameworks/training-and-evaluation-pipelines.md) — Implements training and evaluation pipelines that organize raw data into tensors and batches for model training.
- [Reinforcement Learning](https://awesome-repositories.com/f/artificial-intelligence-ml/reinforcement-learning.md) — Includes the study and practical application of reinforcement learning within the broader deep learning curriculum.

### Development Tools & Productivity

- [Deep Learning Notebooks](https://awesome-repositories.com/f/development-tools-productivity/computational-notebooks/deep-learning-notebooks.md) — Employs interactive deep learning notebooks that combine mathematical theory with executable code and immediate visualization.

### Web Development

- [Model Training Implementations](https://awesome-repositories.com/f/web-development/state-management-models/state-space-models/deep-learning-frameworks/model-training-implementations.md) — Provides source code and notebooks to build and train regression, classification, and generative deep learning models. ([source](https://github.com/dragen1860/deep-learning-with-tensorflow-book#readme))

### Scientific & Mathematical Computing

- [Tensor Computation Graphs](https://awesome-repositories.com/f/scientific-mathematical-computing/high-performance-execution-environments/scientific-computing-platforms/computational-frameworks/tensor-computation-graphs.md) — Implements tensor computation graphs to define and optimize the flow of data through neural network layers.