Torchdata is PyTorch oriented library focused on data processing and input pipelines in general

https://github.com/szymonmaszke/torchdata

Sarbazi, M., Sadeghzadeh, M., & Mir Abedini, S. J. (2019). Improving resource allocation in software-defined networks using clustering. Cluster Computing.
doi:10.1007/s10586-019-02985-3

❇️ @AI_Python_EN

If you just published a paper let us inform other members.
@ai_python_en

Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
pdf: https://arxiv.org/pdf/1909.12224.pdf
abs: https://arxiv.org/abs/1909.12224
project page: https://svip-lab.github.io/project/impersonator.html
github: https://github.com/svip-lab/imper

#AI for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives​. Krzysztof et al explain in the newest Radiology article below.
http://bit.ly/2kULbDz

PyTorch implementations of deep reinforcement learning algorithms and environments

GitHub, by Petros Christodoulou : https://lnkd.in/eRZCQ-d

#pytorch #reinforcementlearning #deeplearning

Google researchers just released #ALBERT , that has beaten all models across various benchmarks.

Also, did you know that most NLP models achieves performance that outpaces average human performance?
——————————————————
ALBERT uses parameter reduction techniques to lower memory consumption and increase the training speed of BERT

1. They topped GLUE ( https://lnkd.in/dkWNRVk ) — 92.2%

2. SQuAD (https://lnkd.in/d_Xrba8 ) leaderboards. — 89.4%

3. RACE - they came third with their ensemble model (https://lnkd.in/d2yWbtC ) — 89.4%
——————————————————
Paper at openreview: https://lnkd.in/dzRvWYS
#deeplearning #machinelearning #NLU #NLG #artificiallintelligence #ai

Artificial Design: Modeling Artificial Super Intelligence with Extended General Relativity and Universal Darwinism via Geometrization for Universal Design Automation

https://openreview.net/forum?id=SyxQ_TEFwS

Bias and Generalization in Deep Generative Models

Blog by Zhao et al.: https://lnkd.in/eRAhsuS

#DeepLearning #GenerativeModels #MachineLearning

Self-Paced Learning:
- supervised method from 2010 #NIPS
- idea: start learning with the easiest samples first and only then learn the difficult ones
- distinct from curriculum learning, where samples are pre-classified to easy/hard: we need to decide the order on our own
sample in a latent model (outliers will be the hardest)
- a better measure (!): how good are the initial predictions for the sample (samples far away from the decision boundary are the easiest).

- for #classification, samples are only easy in context of other samples!
- the set of easy samples is iteratively enlarged
- results: outperforms CCCP in #DNA Motif Finding, handwritten digit recognition and others problems
- link: https://papers.nips.cc/paper/3923-self-paced-learning-for-latent-variable-models

Github has just launched a new NLP/information retrieval challenge: CodeSearchNet challenge. The goal of code search is to retrieve relevant code given natural language. Along with this, they released a huge dataset with: - 6m functions across 6 programming languages (Go, Java, Python etc) - 2m of those 6m functions have associated documentation (docstrings, JavaDoc etc) - And some metadata (line number and more). They also included some baseline models (e.g. BERT-like self-attention model) to help people get started with the challenge. Check it out! #deeplearning #machinelearning


📝 Article: https://lnkd.in/dezzhs9
🔤 Code: https://lnkd.in/dXhRqpE


✴️ @AI_PYTHON_EN

Microsoft open-sourced scripts and notebooks to pre-train and finetune BERT natural language model with domain-specific texts

Github: https://github.com/microsoft/AzureML-BERT


#Bert #Microsoft #NLP #dl

✴️ @AI_PYTHON_EN

Deep Reinforcement Learning
CS 285 at UC Berkeley Lectures will be streamed and recorded.

lectures: https://www.youtube.com/playlist?list=PLkFD6_40KJIwhWJpGazJ9VSj9CFMkb79A

http://rail.eecs.berkeley.edu/deeprlcourse/

✴️ @AI_PYTHON_EN

Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch

https://huggingface.co/transformers

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OpenAI’s GPT-2 Text Generator: Wise As a Scholar

https://www.youtube.com/watch?v=0OtZ8dUFxXA

OpenAI's post:
https://openai.com/blog/gpt-2-6-month-follow-up/

✴️ @AI_Python_en

Free ebooks on Deep Learning

PDFs and epub books on Deep Learning. Make sure you comply with copyrights and use this repository only to get familiar with content and purchasing a legal copy afterward!

Also you should save this link somewhere by forwarding message to your Saved messages (just long tap / click on message and then type ‘Saved messages’ in the dialogue search) or your fellow group, because repo might get shutdown for copyright violation.

Link: https://github.com/ontiyonke/Free-Deep-Learning-Books/tree/master/book

#library #ebook

❇️ @AI_PYTHON_en