Top 22 Python transfer-learning Projects
:mag: Haystack is an open source NLP framework that leverages Transformer models. It enables developers to implement production-ready neural search, question answering, semantic document search and summarization for a wide range of applications.Project mention: Building Dense Passage Retrievers [P] | reddit.com/r/MachineLearning | 2022-04-21
AutoGluon: AutoML for Image, Text, and Tabular DataProject mention: What will the data science job market be like in 5 years? | reddit.com/r/datascience | 2021-08-14
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
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A library for transfer learning by reusing parts of TensorFlow models. (by tensorflow)Project mention: Tensorflow Custom TFLite java.lang.NullPointerException: Cannot allocate memory for the interpreter | reddit.com/r/codehunter | 2022-05-14
I have created a custom tensorflow lite model using retrain.py from https://github.com/tensorflow/hub/blob/master/examples/image_retraining/retrain.py using the following command
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain GeneralizationProject mention: [R] pytorch library for audio/speech domain adaptation? | reddit.com/r/MachineLearning | 2022-03-01
Are there any pytorch libraries to do benchmarking of domain adaptation methods for audio/speech tasks? Something like the Transfer Learning Library (https://github.com/thuml/Transfer-Learning-Library/) for images.
:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.Project mention: Can someone please explain to me the differences between train, dev and test datasets? | reddit.com/r/LanguageTechnology | 2021-09-16
I'm also trying to solve this task in a python notebook (.ipynb) using the FARM framework https://farm.deepset.ai/ and BERT model of huggingface https://huggingface.co/bert-base-uncased
🦄 State-of-the-Art Conversational AI with Transfer Learning
jiant is an nlp toolkit
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Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).Project mention: [P] Deep Learning for time series forecasting (neuralforecast, python package) | reddit.com/r/MachineLearning | 2022-02-07
How does it compare to Flow Forecast? Honestly people rarely mention FF but I've found it much better than pytorch_forecasting and the like.
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-drivingProject mention: Is it possible to train a self driving car on google colab? | reddit.com/r/reinforcementlearning | 2021-09-01
I've been trying for a while now and I started thinking it may not be possible. If anyone has managed to train a self-driving car simulator using openai gym on google colab(preferably), or on any remote server (AWS, GCP, ...) please let me know. So far, I tried carla, airsim, svl, deepdrive and they are all equally useless unless run locally with a gui. I'd really appreciate if someone suggests some way that actually can make it possible.
Finetuning any DNN for better embedding on neural search tasksProject mention: Just released Jina 3.0 - self-hosted AI powered search for any type of data - text, image, gif, audio, video, 3d mesh [Open-Source] | reddit.com/r/selfhosted | 2022-02-27
What exactly you want to do? Search for a particular logo among a large list of files? Jina is the right tool to do that. You can use any deep-learning model of your choice and build the complete search pipeline, then you can fine-tune the model using finetuner, distribute it on kubernetes. I might be getting ahead of myself, what is your use case?
Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystemProject mention: PyKale Preprint: Knowledge-Aware Machine Learning from Multiple Sources in Python [P][R] | reddit.com/r/MachineLearning | 2021-06-29
A 10-page preprint is on arXiv to describe the green machine learning design principles behind our pipeline-based API below as well as features and examples in our PyKale library for multimodal learning and transfer learning with deep learning and dimensionality reduction on graphs, images, texts, and videos to enable and accelerate interdisciplinary research: [2106.09756] PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python (arxiv.org)
Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"Project mention: [R] ResNet strikes back: An improved training procedure in timm. There has been significant progress on best practices for training neural nets since ResNet's introduction in 2015. With such advances, a vanilla ResNet-50 reaches 80.4% top-1 accuracy on ImageNet without extra data or distillation. | reddit.com/r/MachineLearning | 2021-10-04
As far as i know, the assemble-ResNet-50 (https://github.com/clovaai/assembled-cnn) gets 82.8% top-1, though they make some (minor) changes to ResNet-50 architecture.
Towards deepfake detection that actually works (by dessa-oss)
Transfer Learning library for Deep Neural Networks.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
LASER multilingual sentence embeddings as a pip package
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer LearningProject mention: Microsoft's CausalCity | reddit.com/r/CausalInference | 2021-06-30
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]Project mention: [R] Contrastive Visual Representation Learning Is More Robust Than You Might Think (Paper + Analysis) | reddit.com/r/MachineLearning | 2021-06-17
Measuring Massive Multitask Language Understanding | ICLR 2021 (by hendrycks)Project mention: DeepMind's newest language model, Chinchilla (70B parameters), significantly outperforms Gopher (280B) and GPT-3 (175B) on a large range of downstream evaluation tasks | reddit.com/r/singularity | 2022-03-30
Benchmark result is 67.6% which is 7.6% improvement from Gopher. MMLU is multiple choice Q&A over various subjects. Questions can be found linked in this github repo (see data).
Implementation of a Neural Network that can detect whether a video is in-game or notProject mention: I created a video about how you can train a neural network (in python) to learn complex image/video classification tasks (like in-game detection) using transfer learning! The GitHub repo is linked in the video description. Hope this is useful or helpful for some of you guys :-) | reddit.com/r/Python | 2021-06-27
Here’s the GitHub link for anyone else like me who didn’t want to have to go to YouTube to get it.
Determine whether a given video sequence has been manipulated or synthetically generatedProject mention: Detect fake videos using deep learning | news.ycombinator.com | 2022-04-20
Official implementation of AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series DataProject mention: [R] A benchmarking framework for time-series unsupervised domain adaptation | reddit.com/r/MachineLearning | 2022-04-06
Code for https://arxiv.org/abs/2203.08321 found: https://github.com/emadeldeen24/AdaTime
Python transfer-learning related posts
Building Dense Passage Retrievers [P]
1 project | reddit.com/r/MachineLearning | 21 Apr 2022
Dense Passage Retriever(DPR) Open-QA System
1 project | reddit.com/r/LanguageTechnology | 8 Apr 2022
Haystack 1.1 – open source Python framework to build NLP backend applications
1 project | reddit.com/r/programming | 31 Jan 2022
NLP architecture for paragraph extraction based on fixed question
1 project | reddit.com/r/LanguageTechnology | 23 Jan 2022
Show HN: Hello – A conversational search engine powered by transformers
1 project | news.ycombinator.com | 14 Jan 2022
[P] Haystack is an open source NLP framework that leverages Transformer models. It enables developers to implement production-ready neural search, question answering, semantic document search and summarization for a wide range of applications.
1 project | reddit.com/r/MachineLearning | 19 Dec 2021
Haystack - an open source NLP framework that leverages Transformer models. It enables developers to implement production-ready neural search, question answering, semantic document search and summarization for a wide range of applications.
1 project | reddit.com/r/LanguageTechnology | 11 Dec 2021
What are some of the best open-source transfer-learning projects in Python? This list will help you:
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