serving-compare-middleware
d2l-en
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| serving-compare-middleware | d2l-en | |
|---|---|---|
| 1 | 6 | |
| 14 | 21,704 | |
| - | 3.5% | |
| 0.0 | 8.5 | |
| 10 months ago | 8 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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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.
serving-compare-middleware
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A Quantitative Comparison of Serving Platforms for Neural Networks
For this experiment we ran the models (respectively servings) using Docker Compose. You can find the relevant manifests here: https://github.com/Biano-AI/serving-compare-middleware/blob/master/docker-compose.test.yml
d2l-en
- which book to chose for deep learning :lan Goodfellow or francois chollet
- d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
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How to pre-train BERT on different objective tasks using HuggingFace
There might is bert library for pre-train bert model in huggingface, But I suggestion that you train bert model in native pytorch to understand detail, Limu's course is recommended for you
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The Transformer in Machine Translation
GitHub's article on Dive into Deep Learning
- D2l-En
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I created a way to learn machine learning through Jupyter
There are actually some online books and courses built on Jupyter Notebook ([Dive to Deep Learning Book](https://github.com/d2l-ai/d2l-en) for example). However yours is more detail and could really helps beginners.
What are some alternatives?
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
jina - ☁️ Build multimodal AI applications with cloud-native stack
TF-Watcher - Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
transformer-deploy - Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
tritony - Tiny configuration for Triton Inference Server
petastorm - Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.