Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | VTT | Size: 589 MB | Duration: 2 section | 16 lectures | (1h 19m)
What you'll learn

Explore Apache Spark and Machine Learning on the Databricks platform.
Launching Apache Spark Cluster
Process that data using a Machine Learning model (Spark ML Library)
Hands-on learning using the example (Classification and Regression)
Create a Data Pipeline
Real-time Use Case
Publish the Project on Web to Impress your recruiter

Requirements
Apache Spark basic and Scala fundamental knowledge is required and SQL Basics
Following browsers on Windows, Linux or macOS desktop:
Google Chrome (Latest version), Firefox (Latest version), Safari (Latest version), Microsoft Edge* (Latest version)
Internet Explorer 11* on Windows 7, 8, or 10 (with latest Windows updates applied)
*You might see performance degradation for some features on Microsoft Edge and Internet Explorer.
The following browsers are not supported:
Mobile browsers.
Beta, "preview," or otherwise pre-release versions of desktop browsers.
Description
This course attempts to explain the basic concepts of the exponential family of predict modeling. You shall learn about the different components of this family and their relationship. Also, learn about how to identify the right model fitment to the given data series.

One of the most common mistakes an analyst could make during a predictive modeling project is ignorance of sample bias in their data. The cost of making such a mistake can be quite substantial to an organization's business outcome.

In this video course, we will share with you some secrets on how to avoid this mistake. You will learn the following topics:

1) Classification Model

2) Regression Model

Learn the fundamentals of predictive analysis through an easy to understand the conceptual course.

At the end of the class, you should have gained sufficient knowledge to help you detect and reduce sample bias in future predictive modeling or advanced analytics projects.

Predictive Analytics with Apache Spark using Databricks (Unofficial) Notebook (Community edition) including Project

Explore Apache Spark and Machine Learning on the Databricks platform.

Launching Spark Cluster

Create a Data Pipeline

Process that data using a Machine Learning model (Spark ML Library)

Hands-on learning using the example (Classification and Regression)

Real-time Use Case

Publish the Project on Web to Impress your recruiter

Graphical Representation of Data using Databricks notebook.

Transform structured data using SparkSQL and DataFrames

About Databricks:

Databricks lets you start writing Spark ML code instantly so you can focus on your data problems.

Who this course is for:
Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer, Data Scientist, Machine Learning Engineer