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.
Unsupervised Learning with Autoencoders
Explore autoencoder variants, their applications in unsupervised learning, and real-world use cases. Learn about anomaly detection, denoising, and generative models in this comprehensive overview.
The Data Janitor Returns
Practical insights on data-driven decision-making with limited resources. Covers roles, challenges, and real-world solutions in data management, avoiding hype and focusing on impactful strategies.
Mining Software Development History - Approaches and Challenges
Explore software development history analysis, including embeddings, time warping, and clustering techniques. Learn to extract insights from version control logs and predict future trends.
Data to the Rescue! Predicting and Preventing Accidents at Sea
Predicting and preventing maritime accidents using machine learning, leveraging ship behavior data, weather information, and operational profiles to revolutionize the marine insurance industry.
Data to the Rescue - Predicting and Preventing Accidents at Sea
Revolutionizing marine safety through data science: predicting accidents using ship behavior, location, speed, and weather data. Challenges of introducing ML to traditional industry and explaining models with SHAP.
Case Study - Making the Most out of a Doomed Project
Explore strategies for salvaging doomed ML projects, handling challenges, and extracting value from difficult situations in this insightful case study presentation.
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.
First Steps to Interpretable Machine Learning
Explore interpretable machine learning using SHAP values to understand model predictions and feature importance, based on a real data science project with practical insights.
Kotlin for Machine Learning
Explore Kotlin's potential in machine learning projects, from data cleaning to model deployment. Learn about Kotlin tools for data science, including Jupyter notebooks, visualizations, and dataframes.
Filters Beyond OrderBy and LimitTo
Explore advanced uses of AngularJS filters for data transformation, including custom filters and user-driven data manipulation, to enhance application flexibility and user experience.
Angular Material 2 Workshop
Learn to build modern, responsive UIs with Angular Material 2. Explore component libraries, theming, and best practices for creating sleek, efficient Angular applications.
Data Composition with RxJS
Explore advanced RxJS techniques for reactive data handling, including declarative data collection, stream composition, and caching, all without subscriptions.
Getting Started with ag Grid
Comprehensive tutorial on implementing ag-Grid in Angular applications, covering sorting, filtering, custom cell rendering, and infinite scrolling for efficient data management.
Advanced Usage of ag Grid
Explore advanced ag-Grid techniques: NgRx integration with delta row model, custom styling, and building Angular components for rendering, filtering, and editing data in this comprehensive workshop.
4 Wicked RxJS Pipelines for the Real World
Explore four powerful RxJS pipelines for data retrieval and processing, combining Subjects, creation functions, and operators to implement real-world scenarios in Angular applications.
Apache Beam - Making Big Data Portable With gRPC
Explore Apache Beam's unified programming model for efficient, portable data processing pipelines. Learn about its architecture, runners, and gRPC-based portability framework for cross-language execution.
Intro to Falco - Intrusion Detection for Containers
Learn to deploy Falco for container intrusion detection, modify rules, and manage alerts. Discover real-world use cases and best practices from Shopify's experience in securing high-volume cloud environments.
How to Use Kubernetes to Build a Data Lake for AI Workloads
Learn to build a cloud-agnostic data lake using Kubernetes, Rook, and Ceph for AI workloads. Discover how to provide unified data access across multiple data centers for data scientists and developers.
Elephant on Wheels - Petabyte-scale AI @ LinkedIn
Explore LinkedIn's journey in integrating Kubernetes for AI workloads, focusing on secure HDFS access and innovative scheduling solutions for petabyte-scale operations.
Running Big Data Applications at Scale on K8s
Discover how Intuit built a data processing platform using Spark on Kubernetes, reducing costs by 30% and increasing production speed for big data applications at scale.