How to Develop an Intuition for Probability With Worked Examples
https://machinelearningmastery.com/how-to-develop-an-intuition-for-probability-with-worked-examples/
https://machinelearningmastery.com/how-to-develop-an-intuition-for-probability-with-worked-examples/
MachineLearningMastery.com
How to Develop an Intuition for Probability With Worked Examples - MachineLearningMastery.com
Probability calculations are frustratingly unintuitive. Our brains are too eager to take shortcuts and get the wrong answer, instead of thinking through a problem and calculating the probability correctly. To make this issue obvious and aid in developing…
Forwarded from Artificial Intelligence
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/
https://www.youtube.com/watch?v=0OtZ8dUFxXA
OpenAI's post: https://openai.com/blog/gpt-2-6-month-follow-up/
YouTube
OpenAI’s GPT-2 Is Now Available - It Is Wise as a Scholar! 🎓
❤️ Check out Weights & Biases here and sign up for a free demo: https://www.wandb.com/papers
Weights & Biases blog post (the notebook is available too!)
- https://www.wandb.com/articles/visualize-xgboost-in-one-line
- https://colab.research.google.com/d…
Weights & Biases blog post (the notebook is available too!)
- https://www.wandb.com/articles/visualize-xgboost-in-one-line
- https://colab.research.google.com/d…
Releasing PAWS and PAWS-X: Two New Datasets to Improve Natural Language Understanding Models
https://ai.googleblog.com/2019/10/releasing-paws-and-paws-x-two-new.html
PAWS: Paraphrase Adversaries from Word Scrambling
https://arxiv.org/abs/1904.01130
dataset: https://github.com/google-research-datasets/paws
https://ai.googleblog.com/2019/10/releasing-paws-and-paws-x-two-new.html
PAWS: Paraphrase Adversaries from Word Scrambling
https://arxiv.org/abs/1904.01130
dataset: https://github.com/google-research-datasets/paws
Googleblog
Releasing PAWS and PAWS-X: Two New Datasets to Improve Natural Language Understanding Models
❤1
A Gentle Introduction to Bayes Theorem for Machine Learning
https://machinelearningmastery.com/bayes-theorem-for-machine-learning/
https://machinelearningmastery.com/bayes-theorem-for-machine-learning/
Hydra: A framework that simplifies the development of complex applications
https://ai.facebook.com/blog/open-source-in-brief-hydra/
AI RESEARCH, ML APPLICATIONS, OPEN SOURCE
https://engineering.fb.com/open-source/hydra/
code: https://github.com/facebookresearch/hydra/
https://ai.facebook.com/blog/open-source-in-brief-hydra/
AI RESEARCH, ML APPLICATIONS, OPEN SOURCE
https://engineering.fb.com/open-source/hydra/
code: https://github.com/facebookresearch/hydra/
Facebook
Hydra: A framework that simplifies the development of complex applications
Facebook AI is open-sourcing Hydra, a new framework whose dynamic approach to configuration will accelerate the development of complex Python applications.
The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs
https://github.com/rapidsai/cudf
notebooks repo:
https://github.com/rapidsai/notebooks-contrib
API docs
https://docs.rapids.ai/api/cudf/stable/
https://github.com/rapidsai/cudf
notebooks repo:
https://github.com/rapidsai/notebooks-contrib
API docs
https://docs.rapids.ai/api/cudf/stable/
GitHub
GitHub - rapidsai/cudf: cuDF - GPU DataFrame Library
cuDF - GPU DataFrame Library . Contribute to rapidsai/cudf development by creating an account on GitHub.
How to Develop a Naive Bayes Classifier from Scratch in Python
https://machinelearningmastery.com/classification-as-conditional-probability-and-the-naive-bayes-algorithm/
https://machinelearningmastery.com/classification-as-conditional-probability-and-the-naive-bayes-algorithm/
MachineLearningMastery.com
How to Develop a Naive Bayes Classifier from Scratch in Python - MachineLearningMastery.com
Classification is a predictive modeling problem that involves assigning a label to a given input data sample. The problem of classification predictive modeling can be framed as calculating the conditional probability of a class label given a data sample.…
BERT-related Papers
This is a list of BERT-related papers
https://github.com/tomohideshibata/BERT-related-papers
This is a list of BERT-related papers
https://github.com/tomohideshibata/BERT-related-papers
GitHub
GitHub - tomohideshibata/BERT-related-papers: BERT-related papers
BERT-related papers. Contribute to tomohideshibata/BERT-related-papers development by creating an account on GitHub.
BigBiGAN representation learning models
https://arxiv.org/abs/1907.02544
TF Hub: https://tfhub.dev/s?publisher=deepmind&q=bigbigan
Try them out in a Colab at: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/bigbigan_with_tf_hub.ipynb
https://arxiv.org/abs/1907.02544
TF Hub: https://tfhub.dev/s?publisher=deepmind&q=bigbigan
Try them out in a Colab at: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/bigbigan_with_tf_hub.ipynb
arXiv.org
Large Scale Adversarial Representation Learning
Adversarially trained generative models (GANs) have recently achieved compelling image synthesis results. But despite early successes in using GANs for unsupervised representation learning, they...
How to Implement Bayesian Optimization from Scratch in Python
https://machinelearningmastery.com/what-is-bayesian-optimization/
https://machinelearningmastery.com/what-is-bayesian-optimization/
Neural Machine Translation with TensorFlow
https://blog.paperspace.com/neural-machine-translation-with-tensorflow/
https://blog.paperspace.com/neural-machine-translation-with-tensorflow/
Paperspace by DigitalOcean Blog
Neural Machine Translation with TensorFlow
Learn how to build build a recurrent neural network to do French to English translation using Google's open-source machine learning library, TensorFlow.
🔥 PyTorch 1.3 adds mobile, privacy, quantization, and named tensors
https://pytorch.org/blog/pytorch-1-dot-3-adds-mobile-privacy-quantization-and-named-tensors/
github:
https://github.com/pytorch/pytorch/releases/tag/v1.3.0
One simple graphic: Researchers love PyTorch and TensorFlow
https://www.oreilly.com/ideas/one-simple-graphic-researchers-love-pytorch-and-tensorflow
https://pytorch.org/blog/pytorch-1-dot-3-adds-mobile-privacy-quantization-and-named-tensors/
github:
https://github.com/pytorch/pytorch/releases/tag/v1.3.0
One simple graphic: Researchers love PyTorch and TensorFlow
https://www.oreilly.com/ideas/one-simple-graphic-researchers-love-pytorch-and-tensorflow
pytorch.org
An open source machine learning framework that accelerates the path from research prototyping to production deployment.
Forwarded from Artificial Intelligence
Detectron2: A PyTorch-based modular object detection library
https://ai.facebook.com/blog/-detectron2-a-pytorch-based-modular-object-detection-library-/
Detectron2 is FAIR's next-generation research platform for object detection and segmentation
https://github.com/facebookresearch/detectron2
https://ai.facebook.com/blog/-detectron2-a-pytorch-based-modular-object-detection-library-/
Detectron2 is FAIR's next-generation research platform for object detection and segmentation
https://github.com/facebookresearch/detectron2
Meta
Detectron2: A PyTorch-based modular object detection library
We are open-sourcing Detectron2, the second-generation of our widely used object-recognition platform. Detectron2 has been rewritten from the ground up in PyTorch to enable faster model iteration and deployment.
Exploring Massively Multilingual, Massive Neural Machine Translation
https://ai.googleblog.com/2019/10/exploring-massively-multilingual.html
article: https://arxiv.org/pdf/1907.05019.pdf
https://ai.googleblog.com/2019/10/exploring-massively-multilingual.html
article: https://arxiv.org/pdf/1907.05019.pdf
research.google
Exploring Massively Multilingual, Massive Neural Machine Translation
Posted by Ankur Bapna, Software Engineer and Orhan Firat, Research Scientist, Google Research “... perhaps the way [of translation] is to descend...
CrypTen: A new research tool for secure machine learning with PyTorch
https://ai.facebook.com/blog/crypten-a-new-research-tool-for-secure-machine-learning-with-pytorch
code: https://github.com/facebookresearch/CrypTen
https://ai.facebook.com/blog/crypten-a-new-research-tool-for-secure-machine-learning-with-pytorch
code: https://github.com/facebookresearch/CrypTen
Meta
CrypTen: A new research tool for secure machine learning with PyTorch
Facebook AI is open-sourcing CrypTen, a research-focused framework to explore encrypted machine learning techniques in the PyTorch environment.
A Gentle Introduction to Information Entropy
https://machinelearningmastery.com/what-is-information-entropy/
https://machinelearningmastery.com/what-is-information-entropy/
A collection of infrastructure and tools for research in neural network interpretability
https://github.com/tensorflow/lucid
https://github.com/tensorflow/lucid
GitHub
GitHub - tensorflow/lucid: A collection of infrastructure and tools for research in neural network interpretability.
A collection of infrastructure and tools for research in neural network interpretability. - tensorflow/lucid
Forwarded from Artificial Intelligence
Open-sourcing mvfst-rl, a research platform for managing network congestion with reinforcement learning
https://ai.facebook.com/blog/open-sourcing-mvfst-rl-a-research-platform-for-managing-network-congestion-with-reinforcement-learning/
code: https://github.com/facebookresearch/mvfst-rl
https://ai.facebook.com/blog/open-sourcing-mvfst-rl-a-research-platform-for-managing-network-congestion-with-reinforcement-learning/
code: https://github.com/facebookresearch/mvfst-rl
Meta
Open-sourcing mvfst-rl, a research platform for managing network congestion with reinforcement learning
We’re open-sourcing a new platform for experimenting with reinforcement learning to proactively adapt to changing traffic patterns.