Probabilistic Forecasting with DeepAR and AWS SageMaker
Explore probabilistic forecasting with DeepAR, combining deep learning and time series analysis for accurate predictions with uncertainty estimates across multiple related datasets.
Why Transformers Work
Explore the inner workings of transformers in machine learning, their advantages over RNNs, and applications in NLP and dialogue handling, with live demos and clear explanations.
Darts - Unifying Time Series Forecasting Models from ARIMA to Deep Learning
Explore time series forecasting with Darts, a Python library unifying traditional and deep learning models. Learn best practices for preprocessing, backtesting, and achieving quick results in forecasting problems.
Visualizing Data - The Good, the Bad, and the Ugly
Explore effective data visualization techniques, from time series to deviations, using Excel, Power BI, and other tools. Learn to create impactful charts and avoid common pitfalls in data presentation.
Introduction to Time Series Forecasting
Learn intuitive time series forecasting using Microsoft's algorithm in SQL Server Analysis Services. Explore data preparation, model creation, querying, and result interpretation through Visual Studio and Excel demonstrations.
Past to Future - Self-service Forecasting with Microsoft BI
Explore time series forecasting with Microsoft Self-Service BI tools. Learn fundamentals, Excel capabilities, and Power View's predictive analytics for visually impressive forecasts and hindcasts.
Introduction to Data Mining in SQL Server Analysis Services
Learn to create and integrate data mining models in SQL Server Analysis Services for customer prediction, marketing optimization, and forecasting using various algorithms and tools.
Predicting New York City Taxi Demand - Spatio-Temporal Time Series Forecasting
Explore spatio-temporal forecasting for NYC taxi demand using advanced models like LSTM and TCN, reducing prediction errors by 40% compared to baseline methods.
Deep Learning - The Final Frontier for Time Series Analysis
Explore deep learning's potential in time series analysis, covering classification, prediction, and anomaly detection. Learn how neural networks can revolutionize processing of sequential data across various domains.
Scaling to Millions of ML Models to Solve the Problems of SRE and Security
Explore scaling ML models for SRE and security, using open-source technologies to improve zero trust frameworks and infrastructure diagnosis on Kubernetes and service mesh environments.
Intro - Prometheus
Explore Prometheus with maintainers: design, goals, history, and core concepts. Learn about time series, data structure, exposition format, and PromQL query language for effective production use.
Intelligent Analysis on Cloud Infrastructure With AIOps
探索AIOps在云基础设施智能分析中的应用,包括异常检测、资源预测、故障检测和根因分析,以提高云服务管理和运营效率。
Uniting Church and State - FP and OO Together
Explore Church encoding to combine functional and object-oriented programming, achieving simple semantics and high performance in time series analysis for large-scale data processing.
Discovering the True Identity of @horse_js
Uncover the mystery behind @horse_js through data analysis, machine learning, and Azure tools in this entertaining and informative JSConf presentation.
Measure PromQL and MetricsQL Expression Complexity
Explore PromQL/MetricsQL query optimization techniques, including data models, time series analysis, and performance improvement strategies for efficient observability in complex systems.
Processing and Storing Time Series Instrument Data with Pandas and PySpark
Master data processing techniques for handling large-scale time series instrument data using pandas and PySpark, focusing on efficient solutions for scientific and laboratory information management challenges.
Text Prediction Using LSTM
Learn to train LSTM networks for English text prediction, covering data preparation, model architecture, and character-level forecasting techniques.
An Introduction to Forecasting Using Orbit
Explore Orbit, a probabilistic forecasting tool developed by Uber, and learn its application in demand forecasting for technical support teams through a practical case study.
Forecasting Kafka Lag Issues with Machine Learning
Learn to predict and manage Kafka Partition Lag using machine learning techniques. Explore normal and abnormal lag patterns, ensemble forecasting, and case studies for improved Kafka observability.
Scenario Extraction for Self-Driving Vehicles - Real World Applications
Explore real-world scenario extraction for self-driving vehicles. Learn methods to analyze and structure time-series data, classify states and events, and assess traffic behavior for autonomous driving validation.
Feature Estimation for Punching Tool Wear at the Edge
Discover how to monitor punching tool wear through acceleration measurement and edge processing, comparing TSFEL and MiniRocket algorithms for real-time classification of tool conditions in metal manufacturing.