GitLab
GitHub
BitBucket
CircleCI
Gitea
Jenkins
Jira
SourceForge
Google Cloud TPU
Scikit-learn
machine-learning in Python
python-recsys
Qubole
Amazon Forecast
Microsoft Recommendations API
BigML
GitLab Google Cloud TPUGitLab is well-suited for developers, DevOps engineers, project managers, and teams that require robust CI/CD capabilities, strong security features, and an open-source platform that can be self-hosted or used as a cloud service. It is particularly beneficial for organizations looking for a comprehensive solution to streamline their development workflows.
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Based on our record, GitLab should be more popular than Google Cloud TPU. It has been mentiond 144 times since March 2021. 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 use GitHub here as an example, but there are also other hosts you could explore like GitLab and BitBucket. - Source: dev.to / 2 months ago
Expertise. The SaaS provider is declaring: "I am good at XYZ; I can deliver it better than any of my competitors, and I constantly work to improve how I deliver it." Who do you think can better run GitLab, your already overworked Operations team, or GitLab itself? - Source: dev.to / 4 months ago
Integration Capabilities: How easily does it plug into your daily workflow? Look for deep integrations with your IDE, source control (like GitHub or GitLab), and especially your CI/CD pipeline. - Source: dev.to / 5 months ago
Connect your GitLab account for seamless version control. - Source: dev.to / 7 months ago
Web Check CI stands out because it is the first CI/CD module of its kind available for GitLab! It's built on Google's Baseline initiative, the new standard for web platform compatibility. Instead of guessing which features are safe to use, developers get authoritative answers based on real browser support data. - Source: dev.to / 10 months ago
I think the third company (likely Google) is going to make LLMs financially feasible with: - dedicated hardware (https://cloud.google.com/tpu) - optimized models (https://research.google/blog/turboquant-redefining-ai-efficiency-with-extreme-compression/). - Source: Hacker News / about 2 months ago
Previous TPU generations, including last year's Ironwood, were pitched as unified flagship chips. Google's internal experience running Gemini, its consumer AI products, and increasingly complex agent workloads apparently showed that a single architecture forces uncomfortable trade-offs. So they split the roadmap. - Source: dev.to / 3 months ago
Tensor Processing Units are a technology developed and owned by Google. While you can find GPUs in every cloud provider offer, the TPUs are currently only available through Google Cloud Platform. Situation when you invest in a technology or a service that is not available anywhere else is called vendor lock-in โ it's something the sales people love, while customers try to avoid it. What does this look like for... - Source: dev.to / 3 months ago
Google's model is cloud-based. You can't buy a TPU to put in your server. Instead, Google keeps them in their own data centers and rents access exclusively through this. This allows Google to control the entire stack and they don't have to pay the "NVIDIA Tax". - Source: dev.to / 6 months ago
While I don't use Gemini, I'm betting they'll end up being the cheapest in the future because Google is developing the entire stack, instead of relying on GPUs. I think that puts them in a much better position than other companies like OpenAI. https://cloud.google.com/tpu. - Source: Hacker News / 7 months ago
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
machine-learning in Python - Do you want to do machine learning using Python, but youโre having trouble getting started? In this post, you will complete your first machine learning project using Python.
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
python-recsys - python-recsys is a python library for implementing a recommender system.
