Social And Emotional Learning Courses

Databricks

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

Explore end-to-end machine learning with MLflow on Databricks: from data engineering to model deployment, using health data to predict life expectancy through Spark, hyperopt, and interactive dashboards.

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

Databricks

Productionizing Machine Learning Pipelines with Databricks and Azure ML

Jumpstart ML projects with Databricks and Azure ML. Learn to build, track, and deploy production-ready pipelines using tools like MLflow, TensorFlow, and PyTorch for efficient, reproducible data science workflows.

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

Databricks

Deep Learning for Price Action Prediction Using Databricks and AWS

Explore deep learning techniques to enhance price action prediction using Databricks and AWS. Learn to optimize technical indicators and train models with Amazon SageMaker for improved financial forecasting.

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

Databricks

Tuning Machine Learning Models - Scaling, Workflows, and Architecture

Automating and scaling ML model tuning using Hyperopt and Apache Spark. Best practices for workflows, architecture, and optimization in hyperparameter tuning for improved performance and accuracy.

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

Databricks

Productionizing Machine Learning with Microservices Architecture

Learn to deploy ML models as microservices using Spark, enabling auto-scaling, versioning, and security. Discover how to aggregate real-time and historical data for inferencing and create actionable insights.

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

Databricks

State of the Industry - Machine Learning Platforms and MLOps

Explore the state of MLOps and ML platforms with industry leaders, focusing on challenges, common components, and Databricks' approach to unified data analytics and machine learning.

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

Databricks

How to Build a Cloud Data Platform - Machine Learning and Business Intelligence - Part 4

Learn to leverage Delta Lake for dashboards and advanced analytics, enabling downstream teams with machine learning and business intelligence capabilities on a unified data platform.

• YouTube
• 1 hour 59 minutes
• Self-Paced
• Free Video

Databricks

Deep Learning Pipelines for High Energy Physics Using Apache Spark and Distributed Keras

Explore CERN's Apache Spark-based data pipeline for deep learning in High Energy Physics. Learn about distributed training of neural network classifiers using BigDL and Analytics Zoo for improved event filtering at LHC experiments.

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

Databricks

Managing the Complete Machine Learning Lifecycle with MLflow - Part 2

Explore MLflow's capabilities for managing machine learning lifecycles, from data preparation to model deployment, with practical insights on hyperparameter optimization and production workflows.

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

Databricks

Augmenting Machine Learning with Databricks Labs AutoML Toolkit

Explore how Databricks Labs AutoML Toolkit simplifies and optimizes machine learning processes, from data preparation to model optimization, using financial loan risk data examples.

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

Databricks

MLflow and Azure Machine Learning - The Power Couple for ML Lifecycle Management

Explore MLflow and Azure Machine Learning integration for streamlined ML lifecycle management, covering versioning, run history, automation, deployment, and CI/CD pipelines in MLOps.

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

Databricks

Machine Learning at Scale with MLflow and Apache Spark

Explore Société Générale's journey in scaling machine learning, focusing on MLflow and Apache Spark for production deployment, CI/CD pipelines, and overcoming challenges in large-scale ML implementation.

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

Databricks

Scalable AI for Environmental and Social Impact

Explore Microsoft's AI contributions to Apache Spark and Machine Learning, focusing on environmental and social impact projects like art exploration and endangered species protection.

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

Julia Silge

Build Features for Machine Learning from Netflix Description Text

Learn to build machine learning features from Netflix description text and train a support vector machine model using tidymodels, exploring data analysis, feature engineering, and model evaluation techniques.

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

Julia Silge

Subword Features in Machine Learning for Text

Explore machine learning techniques for text analysis using tidymodels to predict Hawaii post offices from their names, with practical code examples and performance evaluation.

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