Introduction

TensorFlow 2.0 is an open-source library for machine learning developed by Google Brain team. It is a flexible and powerful tool for building and training deep learning models, which is widely used for applications such as image recognition, natural language processing, and more.

What’s New in TensorFlow 2.0?

TensorFlow 2.0 introduces several improvements and changes compared to its predecessor, TensorFlow 1.x. Some of the key features include:

• Eager Execution by Default: TensorFlow 2.0 now uses eager execution by default, which eliminates the need to explicitly build and run a computation graph.
• Keras API: TensorFlow 2.0 integrates Keras into the core TensorFlow library, providing a high-level API for building and training models.
• Improved TensorFlow-GPU Integration: TensorFlow 2.0 simplifies the process of using GPU acceleration for training models.

Getting Started with TensorFlow 2.0

To get started with TensorFlow 2.0, you’ll need to install it on your machine. You can do this using pip:

“`bash
pip install tensorflow
“`

Once installed, you can start working with TensorFlow by importing it in your Python script:

“`python
import tensorflow as tf
“`

Conclusion

TensorFlow 2.0 is a powerful, open-source library for machine learning that simplifies the process of building and training deep learning models. Its integration of Keras API, improved GPU integration, and the use of eager execution by default make it an essential tool for any data scientist or machine learning engineer.