Data Science by ODS.ai 🦜
46.1K subscribers
663 photos
77 videos
7 files
1.75K links
First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @malev
加ε…₯钑道
Big article on how #uber ML system Michelangelo works

Michelangelo enables internal teams to seamlessly build, deploy, and operate machine learning solutions at Uber’s scale. It is designed to cover the end-to-end ML workflow: manage data, train, evaluate, and deploy models, make predictions, and monitor predictions. The system also supports traditional ML models, time series forecasting, and deep learning.


Link: https://eng.uber.com/michelangelo/

#ML #MLSystem #MLatwork #practical
πŸ”₯Quasi-Breaking: An Algorithm Inks a Record Deal With Warner Music

Endel uses machine learning to create personalized tracks meant to help people focus, relax and sleep better by inputting factors such as heart rate, time of day, location and weather.
Looking forward to actual music-generating algorithm being signed up for label.

Link: https://hypebeast.com/2019/3/endel-algorithm-record-deal-warner-music

#MLHype #audiolearning #DL #Endel
​​Reducing the Need for Labeled Data in Generative Adversarial Networks

How combination of self-supervision and semi-supervision can help learn from partially labeled data.

Link: https://ai.googleblog.com/2019/03/reducing-need-for-labeled-data-in.html

#GAN #DL #Google #supervisedvsunsupervised
πŸ’«Prefect (Airflow alternative) has gone Open Source

Prefect is capable of:
* Handling data processing timeline
* Orchestrating the backend of Cloud execution platform
* Parameterizing machine learning models
* Execute other ETL patterns

Docs: https://docs.prefect.io
Link: https://medium.com/the-prefect-blog/prefect-is-open-source-744e3c00cf35
GitHub: https://github.com/prefecthq/prefect

#ml_pipeline #mlflow
​​A comprehensive beginner’s guide to create a Time Series Forecast (with Codes in Python)

A middle-level article on #TS forecasting in #Python.

Link: https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/
​​An End-to-End Project on Time Series Analysis and Forecasting with Python

Today’s second article about #TS forecasting, to cover basics and provide knowledge about how to approach TS data mining.

Link: https://towardsdatascience.com/an-end-to-end-project-on-time-series-analysis-and-forecasting-with-python-4835e6bf050b

#Python
Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber

More complex article on #TS forecasting from #Uber team.

Link: https://eng.uber.com/neural-networks-uncertainty-estimation/

#RNN #LSTM #Uber
πŸ’‰Using AI to help increase blood donations

This is a post describing how #Facebook uses #ML and #AI to detect intent or interest in blood donation and to match these people with local hospitals, increasing probability of people actually donating blood. Sounds like an awesome and inspiring application for AI.

Link: https://tech.fb.com/using-ai-to-help-increase-blood-donations/
IPython notebooks and git

#IPython or #Jupyter is one of the most popular tools in Data Science. It usage may questionable, but it is optimal for beginners and people who are making thier first steps. This article covers rare theme β€” keeping notebooks in git repository and optimizing collaboration using them. Main problem lies in technical information (like cell execution count), which is redundant and can be omitted, but still gets written to git in the default scenario.

Link: https://pascalbugnion.net/blog/ipython-notebooks-and-git.html
Code: https://gist.github.com/pbugnion/ea2797393033b54674af

#datascience #practicalML
​​PI-REC: Progressive Image Reconstruction Network With Edge and Color Domain

Paper on how image can be reconstracted from doodle and color palette.

Link: https://arxiv.org/pdf/1903.10146.pdf

#ImageReconstruction #CV #DL
​​Fast video object segmentation with Spatio-Temporal GANs

Spatio-Temporal GANs to the Video Object Segmentation task, allowing to run at 32 FPS without fine-tuning.

#FaSTGAN #GAN #Segmentation #videomining #CV #DL
​​Step Change Improvement in Molecular Property Prediction with PotentialNet

Paper on a significant improvement in ability to predict molecular properties in drug design. #ML algorithms are getting better and better than classical methods.

Link: https://medium.com/@pandelab/step-change-improvement-in-molecular-property-prediction-with-potentialnet-f431ffa32a2c

#drugsdesign #biolearning #healthcare
​​Open-sourcing PyTorch-BigGraph for faster embeddings of extremely large graphs

PyTorch-BigGraphβ€” a tool that for faster and easier producing graph embeddings for extremely large graphs. Outputs high-quality embeddings without specialized computing resources like GPUs or huge amounts of memory.

Link: https://ai.facebook.com/blog/open-sourcing-pytorch-biggraph-for-faster-embeddings-of-extremely-large-graphs/
Github: https://github.com/facebookresearch/PyTorch-BigGraph

#PyTorch #Facebook #OpenSourceRelease #Embeddings #GraphLearning
​​AI talent flow map

Very interesting map of the flow of students between countries on the 2019 Global AI Talent report.

Link: https://jfgagne.ai/talent-2019/
​​Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening

Paper claims model to perform better than human.

ArXiV: https://arxiv.org/abs/1903.08297
GitHub (code & models): https://github.com/nyukat/breast_cancer_classifier

#BreastCaner #healthcare #DL #CV