Social And Emotional Learning Courses

Databricks

Interpretable Machine Learning - Data Brew Season 2 Episode 7

Explore interpretable machine learning with Ameet Talwalkar, discussing its relation to data privacy, fairness, and practical applications in this insightful interview on cutting-edge ML research.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Databricks

Apache Spark, Data Science, and Machine Learning Advances - Data + AI Summit 2021 Keynote

Explore AI advancements, data science, MLOps, and Databricks Lakehouse Platform innovations. Featuring industry leaders and Bill Nye, this keynote covers MLFlow updates, AutoML, and practical machine learning solutions.

• YouTube
• 2 hours 18 minutes
• Self-Paced
• Free Video

Databricks

Developing Scalable Machine Learning Pipelines for Gaming Industry

Explore scalable ML pipelines in gaming, leveraging Apache Spark for data-driven product development and improved user acquisition through advanced LTV modeling.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Databricks

Efficient Query Processing for Unstructured Data Using Machine Learning

Explore efficient query processing techniques for unstructured data using machine learning, including proxy scores and clustering methods to accelerate analysis and reduce costs.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Databricks

Introducing MLflow for End-to-End Machine Learning on Databricks

Learn to predict life expectancy using health data with MLflow. Covers data engineering, exploration, model tuning, and deployment on Databricks' unified analytics platform powered by Apache Spark.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Databricks

Combining Machine Learning and MLflow with Lakehouse Architecture - Data Brew Episode 5

Explore how Quby leverages ML and MLflow with their lakehouse to extract value from IoT sensor data, moving from batch to real-time streaming for energy optimization and customer insights.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

Databricks

MATS Stack for Cross-System Orchestration of Machine Learning Pipelines

Explore the MATS stack for orchestrating ML pipelines across systems, featuring MLFlow, Airflow, Tensorflow, and Spark. Learn how Avast leverages this approach for efficient phishing detection and streamlined ML workflows.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

Databricks

Scaling Machine Learning Feature Engineering in Apache Spark at Facebook

Explore advanced techniques for scaling ML feature engineering in Apache Spark, including Feature Injection and Feature Reaping, with optimizations for improved performance and efficiency at Facebook's scale.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Databricks

MLflow at Company Scale - Scaling and Optimizing for High-Volume Machine Learning

Learn how Criteo scaled MLflow to handle massive data volumes, including horizontal scaling, monitoring, SSO integration, and hadoop cluster integration for data scientists.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Databricks

Taking Machine Learning to Production with MLflow - New Features and Best Practices

Explore MLflow's latest features for productionizing machine learning, including model management, CI/CD, data schemas, and integration with PyTorch for seamless deployment and operation of ML applications.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

Databricks

Taking Deep Learning to Production with MLflow and RedisAI

Explore MLflow and RedisAI integration for efficient deep learning model deployment, featuring multi-framework support, auto-batching, and DAGing capabilities in a reliable runtime environment.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Databricks

User Behavior Hashing for Audience Expansion - Deep Learning Approach

Explore deep learning-based hashing for sequential behavior data, utilizing Spark for large-scale preprocessing and distributed inference on Databricks with Pandas UDF.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Databricks

Fugue: Unifying Big Data Analytics Ecosystems for ETL and Machine Learning

Unifying big data ecosystems with Fugue: SQL-like framework for ETL and ML pipelines, compatible with Spark, TensorFlow, and more. Simplifies development, improves performance, and enhances maintainability.

• YouTube
• 22 minutes
• Self-Paced
• Free Video

Databricks

From Python to PySpark and Back Again - Unifying Single-Host and Distributed Deep Learning with Maggy

Unifying single-host and distributed deep learning with Maggy framework, enabling seamless transition from laptop to cluster for efficient model development and training using TensorFlow and PySpark.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Databricks

Building a Real-Time Feature Store for Machine Learning at iFood

Discover how iFood built a real-time feature store using Databricks and Spark Structured Streaming to process event streams, store data, and develop reliable code for efficient machine learning model predictions.

• YouTube
• 27 minutes
• Self-Paced
• Free Video