Keras Skill
Keras is an open-source high-level neural networks API written in Python. It is designed to be user-friendly, modular, and extensible. Originally developed as an independent library, Keras has been integrated into TensorFlow since TensorFlow 2.0 as the official high-level API. It provides a convenient way to build, train, and deploy deep learning models. Keras provides a high-level interface for building and training neural networks. It abstracts many of the details involved in specifying and training a neural network, making it accessible to beginners while still allowing for advanced customization. Keras allows the construction of neural networks through the use of building blocks called layers. Layers can be combined to create complex network architectures easily. The sequential model and functional API are two ways to construct models in Keras. Keras is designed to be easily extensible. Users can create custom layers, loss functions, and metrics, allowing for the implementation of novel architectures and algorithms. Keras originally supported multiple backend frameworks, including TensorFlow, Theano, and Microsoft Cognitive Toolkit (CNTK). However, since TensorFlow 2.0, Keras has become the official high-level API for TensorFlow.
Keras Sub Skills
Loading Skills...
Loading...
Talend ETL Introduction – Complete Guide for Beginners
Data Science
Data Engineering: DWH and Big Data
Talend ETL Introduction: The Visual Data...
Dimensional Modeling Explained | Data Warehousing Guide
Data Science
Data Engineering: DWH and Big Data
Dimensional Modeling in Data Warehousing: The...
Slowly Changing Dimensions (SCD) Explained | Data Warehousing Guide
Data Science
Data Engineering: DWH and Big Data
Slowly Changing Dimensions (SCD): Preserving...
