Azure Cloud Azure Databricks Apache Spark Machine learning

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1. Introduction

1. Introduction.mp4

04:25

2. What is databricks.mp4

04:43

2. Databricks Quickstart

1. Hands-on How to navigate to the databricks service.mp4

01:40

2.1 databricks-workspace.zip

2. Hands-on How to create a workspace.mp4

03:20

3. Hands-on How to create a spark cluster.mp4

04:48

4. Hands-on How to create a notebook.mp4

00:43

5.1 Databricks-sql.zip

5. Hands-on How to create a table.mp4

00:56

6. Hands-on How to delete a spark cluster.mp4

00:45

7. Hands-on How to delete all resources in Azure Cloud.mp4

05:02

8. What is workspace.mp4

01:44

9. What is Resource Group.mp4

02:39

10.1 Databricks Runtime Note.html

10. What is Databricks Runtime.mp4

01:35

11. What is Cluster.mp4

06:03

3. Apache Spark

1.1 19th ACM Symposium on Operating Systems Principles.html

1.2 google-file-system-session-video.mp4

57:43

1.3 MapReduce Simplified Data Processing on Large Clusters Paper.pdf

1.4 OSDI 04 TECHNICAL SESSIONS.html

1.5 The ACM Digital Library (DL) is the world's most comprehensive database of full-text articles and bibliographic literature covering computing and information technology..html

1.6 The Google File System Paper.pdf

1. History of Hadoop.mp4

15:54

2. What is Apache Spark.mp4

08:14

3. Hands-on Download and install virtualbox.mp4

03:24

4. Hands-on Download and Install putty.mp4

00:59

5. Hands-on Download and Install winscp.mp4

02:17

6.1 HDP download address.html

6. Hands-on How to download HDP.mp4

02:19

7. Hands-on How to set up HDP.mp4

06:21

8.1 hortonworks-hdp2.5-putty.md.zip

8. Hands-on How to SSH into HDP with PuTTY.mp4

01:42

9.1 hortonworks-hdp2.5-winscp.zip

9. Hands-on How to connect to HDP with WinSCP.mp4

01:22

10.1 hortonworks-hdp-web-shell.zip

10. Hands-on How to connect to HDP with Web Shell.mp4

01:05

11.1 Ambari Official website.html

11.2 How-to-use-ambari-to-manage-hadoop.zip

11.3 login credentials.html

11.4 Sandbox Port Forwards.html

11. How to use ambari to manage Hadoop.mp4

05:34

12.1 helloworld.zip

12.2 hortonworks-hdp-Spark-Quick-Start.zip

12. Hands-on Apache Spark Quick Start.mp4

03:52

13.1 TRANSFORMATIONS AND ACTIONS.pdf

13. Apache Spark Architecture.mp4

06:26

14. What is the ecosystem of Apache Spark.mp4

05:11

4. Databricks Developer Tools

1. What is Databricks Developer tools.mp4

06:23

2. Hands-on Download and install python.mp4

02:31

3.1 Databricks-Developer-Tools.zip

3. Hands-on How to set up databricks cli.mp4

06:32

4.1 Databricks-Developer-Tools.zip

4. Hands-on How to use databricks cli.mp4

10:03

5.1 Databricks-Developer-Tools.zip

5. Hands-on How to use Databricks Utilities.mp4

02:49

6. Hands-on Download and install JDK.mp4

03:11

7. Hands-on Download and install IntelliJ IDEA.mp4

05:34

8.1 example-maven.zip

8. Hands-on Using Databricks Utilities API Library in IDE.mp4

16:38

9.1 Databricks-ADF.zip

9. Hands-on How to use databricks in Azure Data Factory.mp4

18:53

10.1 Databricks-ADF.zip

10. Hands-on How to debug the notebook in pipeline.mp4

06:27

11.1 bank.zip

11.2 Databricks-ADF-ETL.zip

11. Hands-on ETL with Azure Databricks.mp4

26:18

12.1 Databricks-ADF-ETL.zip

12. Hands-on How to debug ETL notebook in ETL pipeline.mp4

14:39

5. Databricks Notebook

1. What is notebook.mp4

05:59

2.1 databricks-notebook.zip

2.2 roses.zip

2. Hands-on Using notebook to visualize data.mp4

14:42

6. Databricks Delta Lake

1.1 Set up Apache Spark with Delta Lake.zip

1. Hands-on Set up Apache Spark with Delta Lake.mp4

14:59

2.1 databricks-deltalake-python.zip

2. Hands-on Using python to operate delta lake.mp4

19:19

7. Databricks REST API

1. Hands-on Download and install postman.mp4

02:42

2. Hands-on Generate a token.mp4

00:52

3.1 Databricks-Restful-API.zip

3. Hands-on Create a spark cluster using REST API.mp4

02:03

4.1 Databricks-Restful-API.zip

4. Hands-on Delete a spark cluster using REST API.mp4

02:23

5.1 Databricks-Restful-API.zip

5. Hands-on Permanently delete a spark cluster using REST API.mp4

01:49

8. Databricks Machine Learning

1. History of Artificial Intelligence.mp4

13:12

2. What is Machine Learning.mp4

03:10

3. Workflow of Machine Learning.mp4

12:18

4.1 databricks-ml.zip

4. Hands-on Using scikit-learn with Spark on Databricks.mp4

03:14

5.1 databricks-ml-distribute-parameter-tuning.zip

5. Hands-on Using Spark to distribute parameter tuning.mp4

10:57

6.1 databricks-dl.zip

6. Hands-on Using tensorflow with Spark on Databricks.mp4

14:42

7.1 2018 paper, Demystifying Parallel and Distributed Deep Learning An In-Depth Concurrency Analysis.html

7. Introduction to Distributed Deep Learning.mp4

06:08

8. Distributed methods for using TensorFlow.mp4

05:39

9.1 databricks-dl-distributed.zip

9. Hands-on Distributed deep learning training using TensorFlow with HorovodRunner.mp4

11:25

10.1 databricks-mlflow.zip

10. Hands-on Using MLflow to track parameters and metrics.mp4

12:14

11.1 1993 DBT paper.html

11.2 1993 the earliest cited work.html

11.3 1995 NIPS workshop.html

11.4 1998 springerlink multi-task learning.html

11.5 1998 theoretical foundations of transfer learning.html

11.6 2005 the application of transfer learning in text classification.html

11.7 2007 AAAI.html

11.8 2007 AISTATS conference.html

11.9 2007 Mapping and Revising Markov Logic Networks for Transfer Learning.html

11.10 2007 the application of transfer learning in Bayesian networks.html

11.11 springerlink machine learning.html

11.12 Volume 28, Issue 1, July 1997.html

11. History of Transfer Learning.mp4

11:22

12.1 databricks-transfer-learning.zip

12.2 Runtime.html

12. Hands-on How to perform Transfer Learning on Databricks.mp4

18:20

9. Structured Streaming

1. Hands-on Create a virtual network.mp4

01:50

2.1 HDInsight-kafka.zip

2. Hands-on Create an Kafka cluster on HDInsight.mp4

02:31

3. Hands-on How to connect to kafka using an SSH client.mp4

03:18

4. Hands-on Configure Kafka for IP advertising.mp4

03:02

5. Hands-on Peer the Kafka cluster to the Azure Databricks cluster.mp4

01:37

6. Hands-on Create an Apache Kafka topic.mp4

00:39

7. Hands-on Production Structured Streaming with Kafka.mp4

02:34

8. Hands-on Consumption Structured Streaming with Kafka.mp4

00:37

10. Databricks Graph Analysis

1. History of Graph Analytics.mp4

08:54

2.1 databricks-graph.zip

2. Hands-on How to install dataframes library.mp4

01:49

3.1 databricks-graph.zip

3. Hands-on How to create a graph.mp4

03:13

11. Bonus An Open Source Alternative Solution for Databricks

1. Why use open source alternative solutions.mp4

03:34

2.1 cloudbreak-deployment.zip

2. How to deploy Cloudbreak on Azure Cloud.mp4

32:42

3.1 cloudbreak-deployment.zip

3. Using Cloudbreak to create a cluster.mp4

44:52

Description

Big Data, Spark SQL, Hadoop, Kafka, Data Lake, Transfer Learning, Zeppelin Notebook, Graph, Hortonworks HDP, Cloudbreak

What You'll Learn?

This course will provide you an in depth knowledge of apache Spark and how to work with spark using Azure Databricks
You will understand the main concepts of Azure Cloud
You'll learn about the basic use of Azure Cloud
You will learn to deploy Apache Spark ecosystems locally
You'll learn how to develop a databricks dependency library through IDEA
You will be able to process continual streams of data with Spark streaming
You will learn how to train a machine learning model
You will understand the use case of graph analysis
Deploy Azure Virtual Networks via the Portal
Deploy Azure Resource Groups
You'll learn how to use Azure Data Factory
You'll learn the historical story of Apache Hadoop, Apache Spark and Graph Analysis
You'll learn how to use Apche Zepplin to develop a hello world example of Spark
Deploy Azure Virtual Networks via the Portal

Who is this for?

Anyone who wants to learn Spark, Machine Learning using Azure Databricks

Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer

Students who are willing to learn Azure from ground zero

Students who would like to make a career switch to Microsoft Azure cloud

What You Need to Know?

Apache Spark basic fundamental knowledge is required

Following browsers on Windows and macOS desktop

Free or paid subscription for Microsoft Azure portal.

More details

Description
Microsoft Azure is the fastest growing cloud platform in the world. No prior Azure experience required.
Azure Databricks is unique collaboration between Microsoft and Databricks, forged to deliver Databricksâ€™ Apache Spark-based analytics offering to the Microsoft Azure cloud. With Azure Databricks, you can be developing your first solution within minutes. Azure Databricks is a fast, easy and collaborative Apache Sparkâ€“based analytics service.

Databricks builds on top of Spark and adds:
Â Â Â Highly reliable and performant data pipelines
Â Â Â Productive data science at scale

In this course, you'll have a strong understanding of azure databricks, you will know how to use Spark SQL, Machine Learning, Graph Computing and Structured Streaming Computing in Aziure Databricks.

Why Azure Databricks?
Productive : Launch your new Apache Spark environment in minutes.
Scalable : Globally scale your analytics and machine learning projects.
Trusted : Help protect your data and business with Azure AD integration, role-based controls and enterprise-grade SLAs.
Flexible : Build machine learning and AI solutions with your choice of language and deep learning frameworks.

This course contains both theory lectures ( slides are attached to download for reference) and a significant number of hands-on demos that helps you in gaining hands-on experience. This course help you in laying strong basic foundation in preparation of Microsoft Azure Cloud and Databricks.

In this course, you can not only learn azure databricks, but also learn and practice Machine Learning, Streaming Computing, Graph Analysis, installation and deployment of Open Source Apache spark.
Who this course is for:
Anyone who wants to learn Spark, Machine Learning using Azure Databricks
Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer
Students who are willing to learn Azure from ground zero
Students who would like to make a career switch to Microsoft Azure cloud

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I am a solutions architect, consultant and full stack developer that has a particular interest in all things related to Big Data, Cloud & API, Artificial intelligence.I'm always looking forward to the next challenges. I would really appreciate the chance to share my skills and enthusiasm with you！My favorite programming languages are Scala, Java, Python and Golang.In addition to computer science, I also devote myself to the study of psychology, Big Data in Psychology and Cyberpsychology.

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