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.
YOLOv7, from ML model to ML pipeline, MLOps and ML roadmap, training the YOLOv5, multiplying matrices without multiplying, SoundSpaces platform, the Shapley value in ML, MineDojo, OmniBenchmark, HaGRID, PMData, courses, and more.
Machine Learning & Data Science Survey 2022, how to test ML models in the real world, best practices for deploying language models, neural 3D reconstruction in the wild, mask DINO, MotionCNN, CVNets, StylizedNeRF, courses, tools, and more.
The series of webinars "The A-Z of Data" come back in July, MLOps in 10 minutes, best practices for deploying computer vision models, it is time to explore LCE, graph ordering attention networks, OnePose, Diffuser, Imagen, and more.
MLOps with SageMaker, introduction to the YOLO family, multi GPU model training, neural 3D scene reconstruction with the manhattan-world assumption, learning to answer questions from millions of narrated videos, ConvMAE, ARTEMIS, EasyNLP, and more.
Kubeflow MLOps, a comprehensive list of strategies for feature selection, introducing PyScript, open pre-trained transformer language models, DeepNorm, NeurMiPs, Stanford CS224N NLP with Deep Learning, LAION-5B dataset, and more.
We are excited to get back to work, to revive Data Phoenix from the ashes of war. Today you will know about emerging architectures for modern data infrastructure, backpropagation in RNN, masked generative image transformer, scalable large scene neural view synthesis, and more.
Calculating derivatives in PyTorch, automate your ML development pipeline with PyCaret, a video restoration transformer, adapting CV models for time series and automated EEG review, DALL-Eval, EvoJAX, and more ...
Kubeflow pipeline from scratch, financial text classification using FinBERT, a single model for many visual modalities, a gentle introduction to supervised learning, GAN-based facial editing of real videos, NN-SVG, GreaseLM, Data2vec, videos, and more ...
How to process a dataframe with millions of rows in seconds, calculating derivatives in PyTorch, BERT’s cousin for advanced topic modeling, understanding DBSCAN, convolutional Xformers for vision, transformers in medical imaging, UniFormer, HumanNeRF, Stanford CoreNLP, podcasts, and more ...
Human-like AI avatars by DeepBrain AI, two-dimensional tensors in Pytorch, Unsupervised Reinforcement Learning benchmark, instant neural graphics primitives with a multiresolution hash encoding, a ConvNet for the 2020s, LaMDA, Plenoxel, NeROIC, courses, podcasts, and more ...
Overview of the TOP algorithms for ML, distributed training, capacity recommendation engine, time series anomaly detection with PyFBAD, linear algebra with transformers, a ConvNet for the 2020s, JoJoGAN, Plenoxels, videos, courses, jobs, and more ...