Stars
All the resources you need to get to Senior Engineer and beyond
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
A resource to help you pass system design interview and become good at work 👇
SC23 Deep Learning at Scale Tutorial Material
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Contrastive Learning for Domain Adaptation of Time Series
ULTS: A unified and standardized library of unsupervised representation learning approaches for time series
Domain Adaptation for Time Series Under Feature and Label Shifts
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
LogTAD: Unsupervised Cross-system Log Anomaly Detection via Domain Adaptation (CIKM 2021)
Repository for the MIT Supercloud Dataset
Variational Recurrent Autoencoder for timeseries clustering in pytorch
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
OVIS/LDMS High Performance Computing monitoring, analysis, and visualization project.
AI-Enabling Workloads on Large-Scale GPU-Accelerated System: Characterization, Opportunities, and Implications
NVIDIA Data Center GPU Manager (DCGM) is a project for gathering telemetry and measuring the health of NVIDIA GPUs
Tools for monitoring NVIDIA GPUs on Linux
SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
A Collection of Resources for Weakly-supervised Anomaly Detection (WSAD)
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series" (AAAI 2021)
[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.