TensorFlow

A description of the TensorFlow 2.8 for CPU on Python 3.8 (version 1.0) conda environment.


Released	December 1, 2022
Description	The TensorFlow conda environment is an ecosystem of tools and libraries to create state-of-the-art machine learning models. You can use TensorFlow to train and deploy deep neural networks for image recognition, natural language processing, recurrent neural networks, and other machine learning applications. You use the `oracle-ads` library to speed up your data science workflow. To get started with this conda environment, review the Getting Started notebook, using the Launcher.
Python Version	3.8
Slug	`tensorflow28_p38_cpu_v1`
Object Storage Path	`oci://service-conda-packs@id19sfcrra6z/service_pack/cpu/TensorFlow_2.8_for_CPU_Python_3.8/1.0/tensorflow27_p37_cpu_v1`
Top Libraries	oracle-ads (v2.6.8) pandas (v1.4.4) scikit-learn (v1.1.2) tensorboard (v2.8.0) tensorflow (v2.8.2) transformers (v4.18.0) For a complete list of preinstalled Python libraries, see tensorflow28_p38_cpu_v1.txt.

A description of the TensorFlow 2.16 for GPU on Python 3.10 (version 1.0) conda environment.


Released	August 23, 2024
Description	The TensorFlow conda environment is an ecosystem of tools and libraries to create latest machine learning models. Use TensorFlow to train and deploy deep neural networks for image recognition, natural language processing, recurrent neural networks, and other machine learning applications. Use the `oracle-ads` library to speed up your data science workflow. To get started with the TensorFlow environment for GPUs, open, and , review the notebook example getting-started.ipynb, using the Launcher.
Python Version	3.10
Slug	`tensorflow216_p310_gpu_v1`
Object Storage Path	`oci://service-conda-packs@id19sfcrra6z/service_pack/gpu/TensorFlow_2.16_for_GPU_on_Python_3.10/1.0/tensorflow216_p310_gpu_v1`
Top Libraries	oracle-ads (v2.11.5) pandas (v2.2.2) scikit-learn (v1.5.1) tensorboard (v2.16.2) tensorflow (v2.16.2) transformers (v4.43) For a complete list of preinstalled Python libraries, see tensorflow216_p310_gpu_v1.txt.

A description of the TensorFlow 2.8 for GPU on Python 3.8 (version 1.0) conda environment.


Released	December 1, 2022
Description	The TensorFlow conda environment is an ecosystem of tools and libraries to create state-of-the-art machine learning models. You can use TensorFlow to train and deploy deep neural networks for image recognition, natural language processing, recurrent neural networks, and other machine learning applications. You use the `oracle-ads` library to speed up a data science workflow. To get started with this conda environment, review the Getting Started notebook, using the Launcher.
Python Version	3.8
Slug	`tensorflow28_p38_gpu_v1`
Object Storage Path	`oci://service-conda-packs@id19sfcrra6z/service_pack/GPU/TensorFlow_2.8_for_GPU_Python_3.8/1.0/tensorflow27_p37_gpu_v1`
Top Libraries	oracle-ads (v2.6.8) pandas (v1.5.1) scikit-learn (v1.1.2) tensorboard (v2.8.0) tensorflow (v2.8.1) transformers (v4.18.0) For a complete list of preinstalled Python libraries, see tensorflow28_p38_gpu_v1.txt.