Estimate Change in CEO Departures With Bootstrap Resampling
Explore bootstrap resampling with tidymodels to analyze trends in CEO departures, using generalized linear models and #TidyTuesday data.
Compute Bootstrap Confidence Intervals for Super Bowl Commercial Characteristics
Explore how Super Bowl commercial characteristics evolve over time using tidymodels for bootstrap confidence intervals and data visualization techniques.
Explore Demographic Employment Data With K-Means
Explore employment demographics using k-means clustering to identify similarities across industries and roles, with hands-on data analysis and visualization techniques.
Predict Class Membership for the Datasaurus Dozen With Tidymodels
Explore multiclass evaluation metrics for random forest models using the Datasaurus Dozen dataset, focusing on model performance and visualization techniques.
Impute Missing Data and Handle Class Imbalance for Himalayan Climbing Expeditions
Learn to predict survival in Himalayan climbing expeditions using tidymodels in R. Explore data handling, imputation, and modeling techniques for imbalanced datasets.
Databricks - How to Use Workflows
Learn to orchestrate and schedule complex multi-task processes using Databricks workflows, a powerful extension to the Jobs service that utilizes DAG architecture for efficient data processing and automation.
Data Science: Introduction to Pandas
Explore Pandas for data manipulation: peek, sort, filter, and analyze with mathematical functions, correlation, and covariance.
Data Science Tutorial 1 - Pandas Analysis
Learn to analyze data using Pandas, covering data types, columns, plotting, correlation, and covariance in this comprehensive tutorial.
Data Analysis with Pandas
Learn essential Pandas techniques for data analysis, including data manipulation, correlation analysis, and visualization, to enhance your Python data science skills.
Cyber & Data - What is Data?
Explore data types, formats, and structures in cybersecurity. Learn parsing, encoding, compression, and file analysis techniques for effective data handling and security.
Data & Cyber - Introduction to Data Science
Explore fundamental concepts in data science, including probability, sets, Bayesian theory, correlation, and distribution, to build a strong foundation for advanced analysis.
Getting Started with Jupyter Notebook
Learn to create interactive computational documents with Jupyter Notebook, exploring its architecture, features, and practical applications in data analysis and machine learning.
Pandas UDFs and Python Type Hints in Apache Spark 3.0
Explore redesigned pandas UDFs in Apache Spark 3.0, leveraging Python type hints for clearer, more Pythonic data science workflows and improved static analysis capabilities.
How Adobe Processes 2 Million Records Per Second Using Apache Spark
Explore Adobe's high-performance data processing using Apache Spark, covering optimization techniques, join strategies, structured streaming, skew handling, and integration with Redis for enhanced efficiency.
Accelerating Data Processing in Spark SQL with Pandas UDFs - Optimization Techniques
Learn to optimize Spark SQL data processing using Pandas UDFs. Discover techniques to speed up queries, profile jobs efficiently, and leverage custom UDFs for significant performance gains in large-scale data pipelines.
Apache Spark vs Databricks - On-Premise Performance Comparison
Comparison of on-premise Databricks and open-source Spark implementations, showcasing 10x performance gains in cyber workloads and addressing challenges of air-gapped analytics solutions.
DataSketches: A Production Quality Sketching Library for Big Data Analysis
Explore sketching algorithms for efficient big data analysis, enabling fast approximate answers to complex queries and real-time processing of massive datasets in production environments.
Hyperspace - An Indexing Subsystem for Apache Spark
Explore Hyperspace, an indexing subsystem for Apache Spark that enhances query performance and reduces resource costs. Learn about its design, implementation, and benefits for data analytics on large datasets.
Automating FAA's SWIM Data Ingestion and Analysis with Databricks
Automating FAA's SWIM data ingestion and analysis using cloud-based services, showcasing infrastructure setup, configuration, and insights derived from flight data for improved air transportation management.
Operationalizing Apache Spark MLlib Models with SAS Model Manager
Learn to operationalize Apache Spark MLlib models using SAS Model Manager and Workflow Manager. Discover how to automate and govern the entire model lifecycle, from building to monitoring, accelerating deployment while maintaining control.
Redash - Open Source SQL Analytics on Data Lakes
Explore open-source SQL analytics on data lakes using Redash. Learn to create dashboards, develop workflows, and connect to Databricks for comprehensive analytics with Managed Delta Lake.