Digging into Airbnb data: reviews sentiments, superhosts, and prices prediction (part1)
Example of #AirBnB data research
Link: https://towardsdatascience.com/digging-into-airbnb-data-reviews-sentiments-superhosts-and-prices-prediction-part1-6c80ccb26c6a
Example of #AirBnB data research
Link: https://towardsdatascience.com/digging-into-airbnb-data-reviews-sentiments-superhosts-and-prices-prediction-part1-6c80ccb26c6a
Medium
Digging into Airbnb data: reviews sentiments, superhosts, and prices prediction (part1)
Airbnb is the leading and rapidly growing alternative to the traditional hotel networks. It collects a lot of data about their hosts and…
Building Machine Learning Model From Unstructured Data
https://towardsdatascience.com/building-machine-learning-model-from-unstructured-data-dd2d0263f1db
https://towardsdatascience.com/building-machine-learning-model-from-unstructured-data-dd2d0263f1db
Medium
Building Machine Learning Model From Unstructured Data
You might be familiar with structured data, it is everywhere. Here i would like to focus on discussion on how we transform unstructured…
How linear algebra is applied in machine learning.
When you study an abstract subject like linear algebra, you may wonder: why do you need all these vectors and matrices? Well, if you study it with the purpose of doing ML, this is the answer for you: http://amp.gs/vtWx
When you study an abstract subject like linear algebra, you may wonder: why do you need all these vectors and matrices? Well, if you study it with the purpose of doing ML, this is the answer for you: http://amp.gs/vtWx
Deep Learning and Reinforcement Learning Summer School, Toronto 2018
video:
http://videolectures.net/DLRLsummerschool2018_toronto/
video:
http://videolectures.net/DLRLsummerschool2018_toronto/
Curiosity and Procrastination in Reinforcement Learning
https://ai.googleblog.com/2018/10/curiosity-and-procrastination-in.html
https://ai.googleblog.com/2018/10/curiosity-and-procrastination-in.html
research.google
Curiosity and Procrastination in Reinforcement Learning
Posted by Nikolay Savinov, Research Intern, Google Brain Team and Timothy Lillicrap, Research Scientist, DeepMind Reinforcement learning (RL) is on...
How to analyze “Learning”: Short tour of Computational Learning Theory
https://towardsdatascience.com/how-to-analyze-learning-short-tour-of-computational-learning-theory-9d93b15fc3e5
https://towardsdatascience.com/how-to-analyze-learning-short-tour-of-computational-learning-theory-9d93b15fc3e5
Medium
Reaching for the gut of Machine Learning: A brief intro to CLT
Knowing the fundamentals of the computational learning theory can empower you immensely as a practitioner of machine learning.
Playing Mortal Kombat with TensorFlow.js. Transfer learning and data augmentation
https://blog.mgechev.com/2018/10/20/transfer-learning-tensorflow-js-data-augmentation-mobile-net/
https://blog.mgechev.com/2018/10/20/transfer-learning-tensorflow-js-data-augmentation-mobile-net/
Mgechev
Playing Mortal Kombat with TensorFlow.js. Transfer learning and data augmentation
While experimenting with enhancements of the prediction model of Guess.js, I started looking at deep learning. I’ve focused mainly on recurrent neural networks (RNNs), specifically LSTM because of their “unreasonable effectiveness” in the domain of Guess.js.…
Dimensionality Reduction For Dummies — Part 2: Laying The Bricks
https://towardsdatascience.com/data-science/home
https://towardsdatascience.com/data-science/home
Towards Data Science
Data Science – Towards Data Science
Towards Data Science provides a platform for thousands of people to exchange ideas and to expand our understanding of data science. Your home for data science. A publication sharing concepts, ideas and codes.
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...