Intro to Open Source Observability With Grafana, Prometheus, Loki, and Tempo
Explore open source observability tools like Grafana, Prometheus, Loki, and Tempo. Learn their philosophies, integrations, and best practices for effective monitoring and visualization of complex systems.
Learning from Dependent Data - Lecture 1
Explore techniques for learning from dependent data, focusing on probabilistic and optimization methods in data science. Gain insights into handling interconnected information effectively.
Adapting Kubernetes for Machine Learning Workflows
Explore how Bloomberg adapted Kubernetes for machine learning, addressing multi-tenancy, data security, and hardware acceleration in their AI-driven financial services platform.
xLSTM: Extended Long Short-Term Memory Explained in Detail
Comprehensive exploration of xLSTM architecture, advantages, and applications in sequential data processing, featuring expert insights from Maximilian Beck on this advanced LSTM variant.
Simplicity Bias, Algorithmic Probability, and Time Series in Machine Learning
Explore simplicity bias, algorithmic probability, and time series in this symposium talk on machine learning and dynamical systems.
Learning from Dynamics in Linear Dynamical Systems
Explore efficient algorithms for learning linear dynamical systems, bridging gaps in understanding and revealing connections between machine learning tools and non-stationary settings.
Dynamically Tuning Pods - Leveraging Time Series ML Models with KubeFlow
Explore advanced pod resource optimization using Prometheus and KubeFlow. Learn to implement time series ML models for dynamic tuning in Kubernetes clusters, enhancing performance and efficiency.
Squeeze Your K8s - Adopting Time-Series Forecasting Models in FinOps Practices
Explore time-series forecasting models for optimizing Kubernetes resource allocation, improving cluster utilization, and achieving significant cost savings in cloud-native environments.
Machine Learning with EEG Time-Series - Easy Python Project - Part 0
Learn to classify EEG data between awake and asleep states using Python and random forest. Covers data loading, preprocessing, feature engineering, and machine learning implementation.
Machinery Fault Diagnosis Based on Deep Learning for Time Series Analysis and Knowledge Graphs
Explore deep learning techniques for machinery fault diagnosis using time series analysis and knowledge graphs. Learn data processing, model validation, and ontology modeling for industrial applications.
A Few Quantitative Thoughts on Parking in Marburg - RC3 - 2020
Analyse des données de stationnement à Marburg : tendances, modèles et prévisions pour optimiser l'utilisation des espaces de stationnement et améliorer la planification urbaine.
Evolution of Observability Tools at Pinterest
Explore Pinterest's journey in scaling observability tools, from metrics to log search and distributed tracing, as the company grew from startup to web-scale platform.
Scalable AutoML for Time Series Forecasting Using Ray
Explore scalable AutoML for time series forecasting using Ray, covering feature generation, model selection, and distributed hyper-parameter tuning with real-world applications and insights.
Overview of Automated ML June 2019
Explore automated machine learning for accelerating AI development, with demos on Azure ML Service and Databricks, focusing on Python implementation and recent Azure technologies.
Introduction to Data Analysis with Security Onion and Other Open Source Tools
Learn data analysis techniques for cybersecurity using open-source tools like Security Onion and Python. Explore PANDAS, ElasticSearch, frequency analysis, and time series analysis for effective threat hunting.
How Prometheus Revolutionized Monitoring at SoundCloud
Explore how Prometheus transformed SoundCloud's monitoring, addressing challenges in microservices architecture and offering insights into its implementation, features, and impact on system observability.
Cross-Dataset Time Series Anomaly Detection for Cloud Systems
Innovative approach combining transfer and active learning for detecting anomalies in cloud systems using limited labeled data, improving efficiency in maintaining service availability.
Building Brain-Computer Interfaces with Timeflux
Explore brain-computer interfaces using Timeflux, covering neurophysiology basics, hardware options, and framework architecture. Learn to build processing pipelines and web interfaces for mind-controlled applications.
Time for Time Series
Explore time series analysis fundamentals, decomposition techniques, and forecasting models using Pandas. Learn to extract insights and create powerful predictions from temporal data.
Charlas - Kin Gutierrez Olivares/Federico Garza Ramirez: Nixtla: Deep Learning para pronóstico
Introducción a Nixtla, una librería de Python para pronóstico de series temporales con deep learning. Explora modelos avanzados, aplicaciones comerciales y mejores prácticas para entrenamiento y despliegue.
Deep Learning Your Broadband Network at Home
Automate internet speed tests, log data, and analyze time series using Python. Learn data mining, visualization, and anomaly detection techniques like ARIMA and LSTM for broadband network performance.