Data Phoenix Digest is a collection of the best and latest articles, papers, courses, interviews, podcasts, videos, datasets, events, books, and jobs on Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Science, Robotics and other aspects of Artificial Intelligence.
AI in gaming and energy, an overview of the CVPR 2021, CI/CD for ML online serving and models, BlenderBot 2.0, JupyterLite, TensorRT 8, Color2Style, videos from LOGML summer school, an introduction to Active Learning, datasets, jobs, and more...
Robots that never stumble, AI looks into boiling (yes!), a 3D brain segmentation pipeline for MRI, elastic distributed training with XGBoost on Ray, ClawCraneNet, data science at the command line and more...
ODS.ai Odessa meetup, what is MLOps, advancing AI to make shopping easier for everyone, ChaCha for Online AutoML, AutoFormer, DivergentNets, MultiBERTs, papers from CVPR 2021 and more...
AI that helps write code, EU’s ban on biometric surveillance, genetic algorithms for NLP, multivariate probabilistic regression with NGBoosting, alias-free GAN, MLOps toys, and more...
The impact of NLP and the growing budgets to drive AI transformations. How Airbnb standardized metric computation at scale. Cross-Validation,MASA-SR, AgileGAN, EfficientNetV2, and more...
Facebook AI migrates its systems to PyTorch, metric learning tips & tricks, session-based recommender systems, AndroidEnv, materials from PyCon US 2021, and more...
Machine learning in healthcare, the top 10 TED talks on AI, fraud detection in Uber, DatasetGAN, Text-to-Image generation via transformers, and more...
OpenAI is launching a $100 million startup fund, Albumentations 1.0.0 has been released, lessons on ML platforms, image cropping on Twitter, and more...
PyCaret 101, NVIDIA Deepstream Quickstart, Machine Learning Pipeline Optimization with TPOT, Korean Language Understanding Evaluation, GTC On-Demand, and more...
Release of GPT-Neo, Data Scientist vs Machine Learning Engineer skills, teaching AI how to forget at scale, diffusion models beat GANs on image synthesis, and more...
