models
tensor-house
| models | tensor-house | |
|---|---|---|
| 7 | 4 | |
| 7,192 | 1,163 | |
| 1.4% | - | |
| 4.8 | 7.5 | |
| 11 days ago | 3 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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.
models
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AMD Accelerates AI Adoption on Windows 11 With New Developer Tools for Ryzen AI
Uh, maybe they didn't feel the need to look. I already pointed you to the ONNX project. Here are some ONNX-based. These are just the ones being shared with the community. The limit of AMD's responsibility is writing the low-level libraries to support ONNX.
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Need Help With Darknet YOLOv4-Tiny Model In Unity Barracuda
I am new to object detection models and I need help running my object detection Darknet YOLOv4-Tiny Model In Unity Barracuda. I trained my model and then i converted it to ONNX format with 2 methods. One method was using pytorch-YOLOv4 from github and the other by converting my model to tensorflow and then to onnx and shown here: "https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/yolov4/dependencies/Conversion.ipynb"
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Need Help Converting Darknet Yolov4-tiny Model to ONNX
Then i tried to convert it again using another method that i found here "https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/yolov4/dependencies/Conversion.ipynb" in order to convert it from darknet to tensorflow and then to onnx but i didn't have any luck.
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Text generation with GPT-2 in Ruby
Here we use the GPT-2 model distributed by the ONNX official. Download GPT-2-LM-HEAD from the link.
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YOLOv7 object detection in Ruby in 10 minutes
Download pre-trained models from the ONNX Model Zoo
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Has anyone successfully converted an onnx model to tensorflow? Here's the problems I'm having...
Instructions to reproduce the problem: I am trying to convert a proprietary model at work but for now i'll use mobilenetv2-7.onnx to explain/reproduce the issue.
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How to identify identical frames that are not technically duplicates? Ie if I am taking a video of a car, it stops for 1 minute (and within that minute nothing changes visually), and then drives away. How would I remove all but 1 of the frames when it is stopped?
One approach could be run a pre-trained object detector (like one of these) on each frame and then a simple object tracker on top of it (like this).
tensor-house
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Supply Chain Uses Cases
I still have this on my reading list, it has quite some interesting SC applications. https://github.com/ikatsov/tensor-house
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How to use the code to do analysis with my data
Hi, how can i use the code of an analysis like this https://github.com/ikatsov/tensor-house/blob/master/pricing/price-optimization-multiple-time-intervals.ipynb but with my data?
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What are some applications of Data Science in Digital Marketing?
This is the companion github to the book, it doesn't have all the use cases, but there are a decent amount of code samples to get you started.
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Machine learning Applications in Marketing
Happy to help out! That website I linked has a link to the book PDF, so you can check it out yourself. I guess the Amazon reviews must have missed it, but there is a companion github for a selection of models in the book that may be helpful.
What are some alternatives?
SSD-Mobilenet-Custom-Object-Detector-Model-using-Tensorflow-2 - This repository contains the script and process to create custom SSD Mobilenet model for object detection
EconML - ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
netron - Visualizer for neural network, deep learning and machine learning models
Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
onnx-tensorflow - Tensorflow Backend for ONNX
Workshops - Workshops organized to introduce students to security, AI, blockchain, AR/VR, hardware and software
redisai-examples - RedisAI showcase
models - Models and examples built with TensorFlow
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
vectordb-recipes - High quality resources & applications for LLMs, multi-modal models and VectorDBs
tensorboard - TensorFlow's Visualization Toolkit
mta - Multi-Touch Attribution