Apache Spark Deep Learning Essential Training
42mIntermediate2019-07-01
Authors

Jonathan Fernandes
Consultant focusing on data science, AI, and big data
Course details
Apache Spark is widely considered to be the top platform for professionals needing to glean more comprehensive insights from their data. In this course, explore one of the most exciting aspects of this big data platform—its ability to do deep learning with images. Before he fully delves into deep learning on Spark using Python, instructor Jonathan Fernandes goes over the different ways to do deep learning in Spark, as well as key libraries currently available. He then shows how to set up your Spark deep learning environment, work with images in Spark using the Databricks deep learning library, use a pre-trained model and transfer learning, and deploy models as SQL functions.
Learning objectives
Components in the Apache Spark ecosystem
What is deep learning?
Using deep learning in Spark
Working with images in Spark
Using pre-trained models
Testing your model
Deploying models as SQL functions
Learning objectives
Components in the Apache Spark ecosystem
What is deep learning?
Using deep learning in Spark
Working with images in Spark
Using pre-trained models
Testing your model
Deploying models as SQL functions
Skills covered
Spark DataFramesNeural Networks and Deep LearningData EngineeringEssential TrainingArtificial Intelligence (AI)Data Science
Concepts
0. Introduction
- 01 - Apache Spark
- 02 - What you should know before watching this course
- 03 - Setting up a Databricks account
1. Introduction to Apache Spark
- 04 - Apache Spark ecosystem
- 05 - The origins of Spark and Databricks
2. Deep Learning
- 06 - What is deep learning
- 07 - Using deep learning in Spark
- 08 - Deep learning libraries
3. Working with Images in Spark
- 09 - Setting up a Databricks environment
- 10 - Working with images
4. Pretrained Models and Transfer Learning
- 11 - Using pretrained models
- 12 - What is transfer learning
- 13 - Transfer learning in action
- 14 - Testing your new model
5. Using Models as SQL Functions
- 15 - Deploying models as SQL functions
Conclusion
- 16 - Future project ideas
Related courses
- Building Recommender Systems with Machine Learning and AI
- Cloud Hadoop: Scaling Apache Spark
- Stream Processing Design Patterns with Spark
- Architecting Big Data Applications: Real-Time Application Engineering
- Architecting Big Data Applications: Batch Mode Application Engineering (2017)
- R Programming in Data Science: High Volume Data
- Big Data Analytics with Hadoop and Apache Spark (2020)
- Architecting Big Data Applications: Batch Mode Application Engineering
Related learn paths
- Advance Your Data Skills in Apache Spark
- Moving from Data Scientist to Data Analyst
- Advance Your Skills in the Hadoop/NoSQL Data Science Stack
- Hands-On Data Science
- Explore a Career in Data Engineering
- Prepare for the Databricks Certified Data Engineer Associate Certification
- Advance Your Data Engineering Skills
- Introduction to Fundamental Skills for Data Work: Data Strategy and Planning