TF-Watcher
d2l-en
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TF-Watcher | d2l-en | |
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3 | 6 | |
58 | 21,335 | |
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0.0 | 8.7 | |
11 months ago | 12 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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TF-Watcher
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Tracking mentions began in Dec 2020.
d2l-en
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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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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?
Pytorch-UNet - PyTorch implementation of the U-Net for image semantic segmentation with high quality images
DeepADoTS - Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects
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.
ssd_keras - A Keras port of Single Shot MultiBox Detector
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
ScanRefer - [ECCV 2020] ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language
xgboost_ray - Distributed XGBoost on Ray
textgenrnn - Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
DIML - [ICCV 2021] Towards Interpretable Deep Metric Learning with Structural Matching