Machine Learning with Databricks

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Machine Learning with Databricks

Machine Learning with Databricks

Course ID: DTB-MLD

Duration: 2 Days

Overview

Welcome to Machine Learning with Databricks!
This course is your gateway to mastering machine learning workflows on Databricks. Dive into data preparation, model development, deployment, and operations, guided by expert instructors. Learn essential skills for data exploration, model training, and deployment strategies tailored for Databricks. By course end, you’ll have the knowledge and confidence to navigate the entire machine learning lifecycle on the Databricks platform, empowering you to build and deploy robust machine learning solutions efficiently.

Private in-house training

Apart from public, instructor-led classes, we also offer private in-house trainings for organizations based on their needs. Call us at +852 2116 3328 or email us at [email protected] for more details.

What are the skills covered

Data Preparation for Machine Learning
Machine Learning Model Development
Machine Learning Model Deployment
Machine Learning Operations

Who should attend this course

Everyone who is interested

Course Modules

Module 1: Data Preparation for Machine Learning

Managing and Exploring Data
- Managing and Exploring Data in the Lakehouse
Data Preparation and Feature Engineering
- Fundamentals of Data Preparation and Feature Engineering
- Data Imputation
- Data Encoding
- Data Standardization
Feature Store
- Introduction to Feature Store

Module 2: Machine Learning Model Development

Model Development Workflow
- Model Development and MLflow
- Evaluating Model Performance
Hyperparameter Tuning
- Hyperparameter Tuning Fundamentals
- Hyperparameter Tuning with Hyperopt
AutoML
- Automated Model Development with AutoML

Module 3: Machine Learning Model Deployment

Model Deployment Fundamentals
- Model Deployment Strategies
- Model Deployment with MLflow
Batch Deployment
- Introduction to Batch Deployment
Pipeline Deployment
- Introduction to Pipeline Deployment
Real-time Deployment and Online Stores
- Introduction to Real-time Deployment
- Databricks Model Serving

Module 4: Machine Learning Operations

Modern MLOps
- Defining MLOps
- MLOps on Databricks
Architecting MLOps Solutions
- Opinionated MLOps Principles
- Recommended MLOps Architectures
Implementation and Monitoring MLOps Solution
- MLOps Stacks Overview
- Type of Model Monitoring
- Monitoring in Machine Learning

Prerequisites

At a minimum, you should be familiar with the following before attempting to take this content:

Knowledge of fundamental concepts of regression and classification methods
Knowledge of fundamental machine learning models
Knowledge of the model lifecycle, MLflow components, and MLflow tracking
Familiarity with Databricks workspace and notebooks
Familiarity with Delta Lake and Lakehouse
Intermediate level knowledge of Python

Machine Learning with Databricks