Introducing AdaNet: Fast and Flexible AutoML with Learning Guarantees
https://ai.googleblog.com/2018/10/introducing-adanet-fast-and-flexible.html
https://ai.googleblog.com/2018/10/introducing-adanet-fast-and-flexible.html
Googleblog
Introducing AdaNet: Fast and Flexible AutoML with Learning Guarantees
Semantic Segmentation of Seismic Reflection Images
https://nikolasent.github.io/deeplearning/competitions/2018/10/24/Semantic-Segmentation-of-Seismic-Reflection-Images.html
https://nikolasent.github.io/deeplearning/competitions/2018/10/24/Semantic-Segmentation-of-Seismic-Reflection-Images.html
Computer Vision Lab
Semantic Segmentation of Seismic Reflection Images
A Robotics, Computer Vision and Machine Learning lab by Nikolay Falaleev. The main focus of the blog is application of Deep Learning for Computer Vision tasks, as well as other relevant topics: classical Computer Vision, Numerical Methods and Hardware.
Facebook open sourced Horizon, an end-to-end applied reinforcement learning platform built on #PyTorch 1.0. Horizon uses RL to optimize systems in large-scale production environments and we're excited to make it accessible to anyone using #RL at scale.
https://code.fb.com/ml-applications/horizon/
https://code.fb.com/ml-applications/horizon/
Engineering at Meta
Horizon: The first open source reinforcement learning platform for large-scale products and services
An end-to-end platform built on PyTorch 1.0 that is designed to jump start RL’s transition from research papers to production
❤1
Applying Machine Learning to classify an unsupervised text document
https://towardsdatascience.com/applying-machine-learning-to-classify-an-unsupervised-text-document-e7bb6265f52
https://towardsdatascience.com/applying-machine-learning-to-classify-an-unsupervised-text-document-e7bb6265f52
Medium
Applying Machine Learning to classify an unsupervised text document
Text classification is a problem where we have fixed set of classes/categories and any given text is assigned to one of these categories…
Building client routing / semantic search and clustering arbitrary external corpuses at Profi.ru
https://habr.com/post/428674/
https://habr.com/post/428674/
Хабр
Building client routing / semantic search at Profi.ru
Building client routing / semantic search and clustering arbitrary external corpuses at Profi.ru TLDR This is a very short executive summary (or a teaser) about...
The MAME RL Algorithm Training Toolkit
This Python library has the to potential to train your reinforcement learning algorithm on almost any arcade game. It is currently available on Linux systems and works as a wrapper around MAME. The toolkit allows your algorithm to step through gameplay while recieving the frame data and internal memory address values for tracking the games state, along with sending actions to interact with the game.
https://github.com/M-J-Murray/MAMEToolkit
This Python library has the to potential to train your reinforcement learning algorithm on almost any arcade game. It is currently available on Linux systems and works as a wrapper around MAME. The toolkit allows your algorithm to step through gameplay while recieving the frame data and internal memory address values for tracking the games state, along with sending actions to interact with the game.
https://github.com/M-J-Murray/MAMEToolkit
GitHub
GitHub - M-J-Murray/MAMEToolkit: A Python toolkit used to train reinforcement learning algorithms against arcade games
A Python toolkit used to train reinforcement learning algorithms against arcade games - M-J-Murray/MAMEToolkit
👍1
PyTorch implementation of Google AI's BERT model with a script to load Google's pre-trained models
https://github.com/huggingface/pytorch-pretrained-BERT
https://github.com/huggingface/pytorch-pretrained-BERT
GitHub
GitHub - huggingface/transformers: 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models…
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. - GitHub - huggingface/t...
Using 3D visualizations to tune hyperparameters in ML models
https://towardsdatascience.com/using-3d-visualizations-to-tune-hyperparameters-of-ml-models-with-python-ba2885eab2e9
https://towardsdatascience.com/using-3d-visualizations-to-tune-hyperparameters-of-ml-models-with-python-ba2885eab2e9
Medium
Using 3D visualizations to tune hyperparameters of ML models with Python
Visualizing validation curves can be tricky when we have more than 1 hyperparameter. Here’s how to do it when we have 2, 3 and even more.
Artificial Intelligence meets Art: Neural Transfer Style
https://towardsdatascience.com/artificial-intelligence-meets-art-neural-transfer-style-50e1c07aa7f7
https://towardsdatascience.com/artificial-intelligence-meets-art-neural-transfer-style-50e1c07aa7f7
Medium
Artificial Intelligence meets Art: Neural Transfer Style
Introduction
Kaggle Competition — Image Classification
How to build a CNN model that can predict the classification of the input images using transfer learning
https://towardsdatascience.com/kaggle-competition-image-classification-676dee6c0f23
How to build a CNN model that can predict the classification of the input images using transfer learning
https://towardsdatascience.com/kaggle-competition-image-classification-676dee6c0f23
Medium
Kaggle Competition — Image Classification
To build a model that can predict the classification of the input images
Driving Computer Vision with Deep Learning
https://wayve.ai/blog/2018/10/8/vision-for-driving-with-deep-learning
https://wayve.ai/blog/2018/10/8/vision-for-driving-with-deep-learning
How to train Neural Network faster with optimizers?
https://towardsdatascience.com/how-to-train-neural-network-faster-with-optimizers-d297730b3713
https://towardsdatascience.com/how-to-train-neural-network-faster-with-optimizers-d297730b3713
Medium
How to train Neural Network faster with optimizers?
Mysteries of Neural Networks Part IV
PySyft
PySyft is a Python library for secure, private Deep Learning. PySyft decouples private data from model training, using Multi-Party Computation (MPC) within PyTorch.
https://github.com/OpenMined/PySyft
PySyft is a Python library for secure, private Deep Learning. PySyft decouples private data from model training, using Multi-Party Computation (MPC) within PyTorch.
https://github.com/OpenMined/PySyft
GitHub
GitHub - OpenMined/PySyft: Perform data science on data that remains in someone else's server
Perform data science on data that remains in someone else's server - OpenMined/PySyft
Predicting Professional Players’ Chess Moves with Deep Learning
https://towardsdatascience.com/predicting-professional-players-chess-moves-with-deep-learning-9de6e305109e?source=collection_home---4------0---------------------
https://towardsdatascience.com/predicting-professional-players-chess-moves-with-deep-learning-9de6e305109e?source=collection_home---4------0---------------------
Towards Data Science
Predicting Professional Players’ Chess Moves with Deep Learning
So I’m bad at chess.