AutoDeploy VS Deep-Learning-In-Production

Compare AutoDeploy vs Deep-Learning-In-Production and see what are their differences.

AutoDeploy

AutoDeploy is a single configuration deployment library (by kartik4949)
Tensorflow Deployment Deployment Automation monioring
Source Code
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Deep-Learning-In-Production

Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples. (by The-AI-Summer)
Machine Learning Production Deep Learning AI Tensorflow neural-network Python Deployment Cloud Training Unet semantic-segmentation machinelearningproject Deeplearning
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amzn.to
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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.
www.influxdata.com
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AutoDeploy Deep-Learning-In-Production
3 2
41 1,073
- 0.8%
5.7 0.0
over 2 years ago about 1 year ago
Jupyter Notebook Jupyter Notebook
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

AutoDeploy

Posts with mentions or reviews of AutoDeploy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-10.

Deep-Learning-In-Production

Posts with mentions or reviews of Deep-Learning-In-Production. We have used some of these posts to build our list of alternatives and similar projects.
  • [P] Deep Learning in Production Book
    1 project | /r/MachineLearning | 30 Nov 2021
    The book is based on an old articles series we wrote on our blog so a big portion of the content is already available for free. We just organized/restructured some of the articles and we added some new material. We use a variety of examples with libraries such as Tensorflow, Flask, uWSGI, Nginx, Docker, Kubernetes, Tensorflow Extended, Google Cloud, Vertex AI. The full code and the articles can be found on Github (https://github.com/The-AI-Summer/Deep-Learning-In-Production)
  • [D] Deep learning in Production
    1 project | /r/MachineLearning | 8 Mar 2021

What are some alternatives?

When comparing AutoDeploy and Deep-Learning-In-Production you can also consider the following projects:

cartoonify - Deploy and scale serverless machine learning app - in 4 steps.

strv-ml-mask2face - Virtually remove a face mask to see what a person looks like underneath

ArtLine - A Deep Learning based project for creating line art portraits.

PConv-Keras - Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai

practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book

Human-Segmentation-PyTorch - Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos

TrainInvaders - 👾 Jupyter Notebook + Space Invaders!?

TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0

learnopencv - Learn OpenCV : C++ and Python Examples

MetaSpore - A unified end-to-end machine intelligence platform

unet - unet for image segmentation

AutoDeploy vs cartoonify Deep-Learning-In-Production vs strv-ml-mask2face Deep-Learning-In-Production vs ArtLine Deep-Learning-In-Production vs PConv-Keras Deep-Learning-In-Production vs practical-mlops-book Deep-Learning-In-Production vs Human-Segmentation-PyTorch Deep-Learning-In-Production vs TensorFlow-Tutorials Deep-Learning-In-Production vs TrainInvaders Deep-Learning-In-Production vs TensorFlow2.0_Notebooks Deep-Learning-In-Production vs learnopencv Deep-Learning-In-Production vs MetaSpore Deep-Learning-In-Production vs unet