Best of Machine Learning in 2019: Reddit Edition
https://heartbeat.fritz.ai/best-of-machine-learning-in-2019-reddit-edition-5fbb676a808
https://heartbeat.fritz.ai/best-of-machine-learning-in-2019-reddit-edition-5fbb676a808
Fritz ai
Best of Machine Learning in 2019: Reddit Edition - Fritz ai
To help sift through some of the incredible projects, research, demos, and more in 2019, here’s a look at 17 of the most popular and talked-about projects in machine learning, curated from the r/MachineLearning subreddit. I hope you find something… Continue…
TensorFlow 2 Tutorial: Get Started in Deep Learning With tf.keras
https://machinelearningmastery.com/tensorflow-tutorial-deep-learning-with-tf-keras/
https://machinelearningmastery.com/tensorflow-tutorial-deep-learning-with-tf-keras/
MachineLearningMastery.com
TensorFlow 2 Tutorial: Get Started in Deep Learning with tf.keras - MachineLearningMastery.com
Predictive modeling with deep learning is a skill that modern developers need to know. TensorFlow is the premier open-source deep learning framework developed and maintained by Google. Although using TensorFlow directly can be challenging, the modern tf.keras…
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
https://eng.uber.com/generative-teaching-networks/
Paper: https://arxiv.org/abs/1912.07768
https://eng.uber.com/generative-teaching-networks/
Paper: https://arxiv.org/abs/1912.07768
Uber Blog
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data | Uber Blog
Generative Teaching Networks (GANs) automatically generate training data, learning environments, and curricula to help AI agents rapidly learn.
VizSeq: A visual analysis toolkit for accelerating text generation research
https://ai.facebook.com/blog/vizseq-a-visual-analysis-toolkit-for-accelerating-text-generation-research/
Code: https://github.com/facebookresearch/vizseq
Learn more about Vizseq :
https://facebookresearch.github.io/vizseq/
https://ai.facebook.com/blog/vizseq-a-visual-analysis-toolkit-for-accelerating-text-generation-research/
Code: https://github.com/facebookresearch/vizseq
Learn more about Vizseq :
https://facebookresearch.github.io/vizseq/
Facebook
VizSeq: A visual analysis toolkit for accelerating text generation research
VizSeq is a Python toolkit that provides a scalable solution for visual analysis on text generation tasks.
ALBERT: A Lite BERT for Self-Supervised Learning of Language Representations
https://ai.googleblog.com/2019/12/albert-lite-bert-for-self-supervised.html
Github: https://github.com/google-research/ALBERT
https://ai.googleblog.com/2019/12/albert-lite-bert-for-self-supervised.html
Github: https://github.com/google-research/ALBERT
research.google
ALBERT: A Lite BERT for Self-Supervised Learning of Language Representations
Posted by Radu Soricut and Zhenzhong Lan, Research Scientists, Google Research Ever since the advent of BERT a year ago, natural language research...
A new open benchmark for speech recognition with limited or no supervision
https://ai.facebook.com/blog/a-new-open-benchmark-for-speech-recognition-with-limited-or-no-supervision/
Code and dataset: https://ai.facebook.com/tools/libri-light
Full paper: https://arxiv.org/abs/1912.07875
https://ai.facebook.com/blog/a-new-open-benchmark-for-speech-recognition-with-limited-or-no-supervision/
Code and dataset: https://ai.facebook.com/tools/libri-light
Full paper: https://arxiv.org/abs/1912.07875
Meta
A new open benchmark for speech recognition with limited or no supervision
Facebook AI has released Libri-light, the largest open source dataset for speech recognition to date. This new benchmark helps researchers pretrain acoustic models to understand speech, with few to no labeled examples.
Speeding up model with fusing batch normalization and convolution
https://learnml.today/speeding-up-model-with-fusing-batch-normalization-and-convolution-3
https://learnml.today/speeding-up-model-with-fusing-batch-normalization-and-convolution-3
Using a Convolutional Neural Network to Play Conway's Game of Life with Keras
https://kylewbanks.com/blog/conways-game-of-life-convolutional-neural-network-keras
GIthub: https://github.com/KyleBanks/conways-gol-cnn
Habr: https://habr.com/ru/post/481544/
@ai_machinelearning_big_data
https://kylewbanks.com/blog/conways-game-of-life-convolutional-neural-network-keras
GIthub: https://github.com/KyleBanks/conways-gol-cnn
Habr: https://habr.com/ru/post/481544/
@ai_machinelearning_big_data
Kyle Banks
Using a Convolutional Neural Network to Play Conway's Game of Life with Keras
The goal of this post is to train a convolutional neural network to properly play Conway’s Game of Life without explicitly teaching it the rules of the game.
Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet
https://github.com/horovod/horovod
https://lfai.foundation/press-release/2018/12/13/lf-deep-learning-welcomes-horovod-distributed-training-framework-as-newest-project/
https://github.com/horovod/horovod
https://lfai.foundation/press-release/2018/12/13/lf-deep-learning-welcomes-horovod-distributed-training-framework-as-newest-project/
GitHub
GitHub - horovod/horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. - horovod/horovod
RepPoints: Point Set Representation for Object Detection
Github: https://github.com/microsoft/RepPoints
Article: https://arxiv.org/abs/1904.11490
@ai_machinelearning_big_data
Github: https://github.com/microsoft/RepPoints
Article: https://arxiv.org/abs/1904.11490
@ai_machinelearning_big_data
GitHub
GitHub - microsoft/RepPoints: Represent Visual Objects by Point Sets
Represent Visual Objects by Point Sets. Contribute to microsoft/RepPoints development by creating an account on GitHub.
HSE Faculty of Computer Science and Yandex launch registration for the 3rd International Data Analysis Olympiad (IDAO 2020)
⚡️The platinum partner of IDAO 2020 is QIWI Russia
The Olympiad includes 2 parts:
📍Online Stage, 15 January – 11 February2020
📍Offline stage (Final), which will be held on 2–5 April in Yandex office, Moscow.
🌟We are calling for the world’s best teams!
Winners and prize-holders of IDAO 2020 will receive valuable prizes and gifts.
Learn more: https://idao.world/
⚡️The platinum partner of IDAO 2020 is QIWI Russia
The Olympiad includes 2 parts:
📍Online Stage, 15 January – 11 February2020
📍Offline stage (Final), which will be held on 2–5 April in Yandex office, Moscow.
🌟We are calling for the world’s best teams!
Winners and prize-holders of IDAO 2020 will receive valuable prizes and gifts.
Learn more: https://idao.world/
Develop an Intuition for Severely Skewed Class Distributions
https://machinelearningmastery.com/how-to-develop-an-intuition-skewed-class-distributions/
https://machinelearningmastery.com/how-to-develop-an-intuition-skewed-class-distributions/
MachineLearningMastery.com
Develop an Intuition for Severely Skewed Class Distributions - MachineLearningMastery.com
An imbalanced classification problem is a problem that involves predicting a class label where the distribution of class labels in the training dataset is not equal. A challenge for beginners working with imbalanced classification problems is what a specific…
WELCOME TO THE DALI DATASET: a large Dataset of synchronised Audio, LyrIcs and vocal notes.
https://github.com/gabolsgabs/DALI
Paper: https://ismir2018.ircam.fr/doc/pdfs/35_Paper.pdf
Learning Singing From Speech
https://arxiv.org/abs/1912.10128v1
https://github.com/gabolsgabs/DALI
Paper: https://ismir2018.ircam.fr/doc/pdfs/35_Paper.pdf
Learning Singing From Speech
https://arxiv.org/abs/1912.10128v1
GitHub
GitHub - gabolsgabs/DALI: DALI: a large Dataset of synchronised Audio, LyrIcs and vocal notes.
DALI: a large Dataset of synchronised Audio, LyrIcs and vocal notes. - gabolsgabs/DALI
✏️ Multi-Graph Transformer for Free-Hand Sketch Recognition
https://github.com/PengBoXiangShang/multigraph_transformer
Paper: https://arxiv.org/abs/1912.11258v1
https://github.com/PengBoXiangShang/multigraph_transformer
Paper: https://arxiv.org/abs/1912.11258v1
GitHub
GitHub - PengBoXiangShang/multigraph_transformer: IEEE TNNLS 2021, transformer, multi-graph transformer, graph, graph classification…
IEEE TNNLS 2021, transformer, multi-graph transformer, graph, graph classification, sketch recognition, sketch classification, free-hand sketch, official code of the paper "Multi-Graph Tr...
🍌 BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
article: https://arxiv.org/abs/1910.11858
code: https://github.com/naszilla/bananas
medium: https://medium.com/reality-engines/bananas-a-new-method-for-neural-architecture-search-192d21959c0c
article: https://arxiv.org/abs/1910.11858
code: https://github.com/naszilla/bananas
medium: https://medium.com/reality-engines/bananas-a-new-method-for-neural-architecture-search-192d21959c0c
GitHub
GitHub - naszilla/bananas: Bayesian Optimization with Neural Architectures for Neural Architecture Search - https://arxiv.org/abs/1910.11858
Bayesian Optimization with Neural Architectures for Neural Architecture Search - https://arxiv.org/abs/1910.11858 - naszilla/bananas
Audio processing by using pytorch 1D convolution network
https://github.com/KinWaiCheuk/nnAudio
nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolution Neural Networks
https://arxiv.org/abs/1912.12055v1
https://github.com/KinWaiCheuk/nnAudio
nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolution Neural Networks
https://arxiv.org/abs/1912.12055v1
GitHub
GitHub - KinWaiCheuk/nnAudio: Audio processing by using pytorch 1D convolution network
Audio processing by using pytorch 1D convolution network - KinWaiCheuk/nnAudio
Integration of Static and Dynamic Analysis for Malware Family Classification with Composite Neural Network
code: https://github.com/guelfoweb/peframe
Paper: https://arxiv.org/abs/1912.11249v1
code: https://github.com/guelfoweb/peframe
Paper: https://arxiv.org/abs/1912.11249v1
GitHub
GitHub - guelfoweb/peframe: PEframe is a open source tool to perform static analysis on Portable Executable malware and malicious…
PEframe is a open source tool to perform static analysis on Portable Executable malware and malicious MS Office documents. - guelfoweb/peframe
Recurrent Independent Mechanisms
Code: https://github.com/maximecb/gym-minigrid
Paper: https://openreview.net/forum?id=BylaUTNtPS
Code: https://github.com/maximecb/gym-minigrid
Paper: https://openreview.net/forum?id=BylaUTNtPS
GitHub
GitHub - Farama-Foundation/Minigrid: Simple and easily configurable grid world environments for reinforcement learning
Simple and easily configurable grid world environments for reinforcement learning - Farama-Foundation/Minigrid
How to Calculate Precision, Recall, and F-Measure for Imbalanced Classification
https://machinelearningmastery.com/precision-recall-and-f-measure-for-imbalanced-classification/
https://machinelearningmastery.com/precision-recall-and-f-measure-for-imbalanced-classification/
MachineLearningMastery.com
How to Calculate Precision, Recall, and F-Measure for Imbalanced Classification - MachineLearningMastery.com
Classification accuracy is the total number of correct predictions divided by the total number of predictions made for a dataset. As a performance measure, accuracy is inappropriate for imbalanced classification problems. The main reason is that the overwhelming…
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia
https://openreview.net/forum?id=rkeYL1SFvH
LASER Language-Agnostic SEntence Representations
https://github.com/facebookresearch/LASER
https://openreview.net/forum?id=rkeYL1SFvH
LASER Language-Agnostic SEntence Representations
https://github.com/facebookresearch/LASER
OpenReview
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs...
Large-scale bitext extraction from Wikipedia: 1620 language pairs in 85 languages, 135M parallel sentences, Systematic NMT evaluation on TED test set.