Ansible
Chef
Jenkins
Terraform
Puppet Enterprise
Codeship
CircleCI
Octopus Deploy
PyTorch
TensorFlow
Keras
Scikit-learn
OpenCV
CUDA
NumPy
Pandas
Ansible PyTorchBased on our record, PyTorch seems to be a lot more popular than Ansible. While we know about 106 links to PyTorch, we've tracked only 9 mentions of Ansible. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
We are open to practice using any open-source project, however, we want to set a sharp focus on projects maintained by the Red Hat, and our own projects in the Caravana Cloud organization on github. If there is no reason to do differently, we'll build using technologies such as OpenShift, Quarkus, Ansible and related projects. - Source: dev.to / 11 months ago
*Codifying the deployment of the OTel Collector *(to Nomad, Kubernetes, or a VM) using tools such as Terraform, Pulumi, or Ansible. The Collector funnels your OTel data to your Observability back-end. ✅. - Source: dev.to / almost 2 years ago
Most of what I've learnt today was purley from this blog and only because it's from ansible.com - dated now I guess ... Source: almost 2 years ago
I installed the helm release using Ansible, but you can install with the following helm commands:. - Source: dev.to / almost 2 years ago
[root@ansible ~]# pip show ansible Name: ansible Version: 2.9.25 Summary: Radically simple IT automation Home-page: https://ansible.com/ Author: Ansible, Inc. Author-email: info@ansible.com License: GPLv3+ Location: /usr/lib/python2.7/site-packagesRequires: jinja2, PyYAML, cryptography Required-by:. Source: over 2 years ago
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / 27 days ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / 2 months ago
Import torch # we use PyTorch: https://pytorch.org Data = torch.tensor(encode(text), dtype=torch.long) Print(data.shape, data.dtype) Print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this. - Source: dev.to / 3 months ago
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries. - Source: dev.to / 2 months ago
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework. - Source: dev.to / 2 months ago
Chef - Automation for all of your technology. Overcome the complexity and rapidly ship your infrastructure and apps anywhere with automation.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Terraform - Tool for building, changing, and versioning infrastructure safely and efficiently.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.