English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 0h 42m | 98 MB
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.
Topics include:
- 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
Table of Contents
Introduction
1 Apache Spark
2 What you should know before watching this course
3 Setting up a Databricks account
Introduction to Apache Spark
4 Apache Spark ecosystem
5 The origins of Spark and Databricks
Deep Learning
6 What is deep learning
7 Using deep learning in Spark
8 Deep learning libraries
Working with Images in Spark
9 Setting up a Databricks environment
10 Working with images
Pretrained Models and Transfer Learning
11 Using pretrained models
12 What is transfer learning
13 Transfer learning in action
14 Testing your new model
Using Models as SQL Functions
15 Deploying models as SQL functions
Conclusion
16 Future project ideas
Resolve the captcha to access the links!