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Top 16 Go Deep Learning Projects
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determined
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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tensor
package tensor provides efficient and generic n-dimensional arrays in Go that are useful for machine learning and deep learning purposes
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llama-nuts-and-bolts
A holistic way of understanding how LLaMA and its components run in practice, with code and detailed documentation.
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distributed-inference
A project to demonstrate an approach to designing cross-language and distributed pipeline in deep learning/machine learning domain, using WebRTC and Redis Streams.
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17. Determined AI | Github | tutorial
https://github.com/vearch/vearch/blob/master/engine/index/RE...
tldr; you should start with KubeFlow 99% of the time. The respective job scheduling workflows (including volano) can be managed with Kubeflow Arena. Vulcano is ok, but I personally prefer Nvidia's Merlin + Triton inference on top of ONNX and MS ONNX Runtime. I do like to train with GPU's on Merlin in GKE (TabularNV and HugeCTR's tbe), and run TFKeras ReLu models on CPU's with OpenVino on AWS EKS, to optimize costs a bit. I do use Kubeflow on top of TektonCD for OpenShift, while some folks do prefer Argo Workflows and Apache Airflow, in the end - it's all DAG pipelines, so doesn't really matter.
Project mention: How to create YOLOv8-based object detection web service using Python, Julia, Node.js, JavaScript, Go and Rust | dev.to | 2023-05-13If you like to work with this output in a more convenient "Pythonic" way, there is a Gorgonia Tensor library that emulates features of NumPy in Go. You can use it to physically reshape the output to 84x400, then transpose to 8400x84 and then traverse detected objects by row.
Project mention: Show HN: LLaMA Nuts and Bolts, A holistic way of understanding how LLMs run | news.ycombinator.com | 2024-03-20
Go Deep Learning related posts
- Open Source Ascendant: The Transformation of Software Development in 2024
- Show HN: Carton – Run any ML model from any programming language
- Handling concurrent requests to ML model API
- Ask HN: How do you stay on top of advances in AI?
- Volcano vs Yunikorn vs Knative
- Coding your own AI in 2023 with fastai
- Nos – Open-Source to Maximize GPU Utilization in Kubernetes
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A note from our sponsor - SaaSHub
www.saashub.com | 26 Apr 2024
Index
What are some of the best open-source Deep Learning projects in Go? This list will help you:
Project | Stars | |
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1 | Gorgonia | 5,333 |
2 | determined | 2,851 |
3 | vearch | 1,904 |
4 | aistore | 1,089 |
5 | arena | 702 |
6 | go-deep | 516 |
7 | gotch | 507 |
8 | tensor | 338 |
9 | cybertron | 258 |
10 | go-ctr | 223 |
11 | tokenizer | 136 |
12 | llama-nuts-and-bolts | 103 |
13 | gan-go | 83 |
14 | verbaflow | 57 |
15 | distributed-inference | 46 |
16 | goslide | 39 |
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