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Scala and Spark for Big Data and Machine Learning

Scala and Spark for Big Data and Machine Learning

Loại khoá học: Programming Languages

Learn the latest Big Data technology - Spark and Scala, including Spark 2.0 DataFrames!

image
50.000 VND
1.099.000 VND
Đầy Đủ Bài Giảng
Học Online Tiện Lợi
Kích Hoạt Nhanh 2-5 Phút
Thanh toán tự động
Được phép tải xuống

Tổng quan

Nội dung khoá học

Đánh giá

Mô tả

Learn how to utilize some of the most valuable tech skills on the market today, Scala and Spark! In this course we will show you how to use Scala and Spark to analyze Big Data.

Scala and Spark are two of the most in demand skills right now, and with this course you can learn them quickly and easily! This course comes packed with content:

  • Crash Course in Scala Programming
  • Spark and Big Data Ecosystem Overview
  • Using Spark's MLlib for Machine Learning 
  • Scale up Spark jobs using Amazon Web Services
  • Learn how to use Databrick's Big Data Platform
  • and much more!

This course comes with full projects for you including topics such as analyzing financial data or using machine learning to classify Ecommerce customer behavior! We teach the latest methodologies of Spark 2.0 so you can learn how to use SparkSQL, Spark DataFrames, and Spark's MLlib!

After completing this course you will feel comfortable putting Scala and Spark on your resume!

Thanks and I will see you inside the course!

Bạn sẽ học được gì

Use Scala for Programming

Use Spark 2.0 DataFrames to read and manipulate data

Use Spark to Process Large Datasets

Understand hot to use Spark on AWS and DataBricks

Yêu cầu

  • Basic Programming Knowledge in some language
  • Basic Math Skills
  • English Language

Nội dung khoá học

17 sections

Course Introduction

3 lectures
Introduction
02:28
Course FAQs
00:13
Scala and Spark Overview
10:40

Scala IDE Options and Overview

2 lectures
ScalaIDE Overview
02:51
Computer Set-up Time!
00:17

Windows Scala and Spark Set-up and Installation

5 lectures
Windows Introduction
00:40
Quick note about Windows Installation.
00:17
Windows Scala and Spark Installation
12:09
Atom Windows Installation
09:30
Terminal Exericse
00:35

Mac OS Setup and Installation

1 lectures
Mac OS Installation and Setup
09:57

Linux (Ubuntu) Setup and Installation

1 lectures
Installing Scala and Spark on Linux (Ubuntu)
12:49

Scala Programming: Level One

8 lectures
Arithmetic and Numbers
07:00
Values and Variables
07:49
Booleans and Comparison Operators
02:11
Strings and Basic Regex
12:48
Tuples
02:35
Scala Basics - Assessment Test Exercises
00:38
Scala Basics Assessment Test Questions
00:25
Scala Basics - Assessment Test Solutions
05:53

Collections

8 lectures
Intro to Collections
00:47
Lists
08:28
Arrays
03:48
Sets
06:02
Maps
07:18
Collections - Assessment Test Exercise
00:30
Scala Collections Assessment Test
00:26
Collections Assessment Test - Solutions
06:14

Scala Programming: Level Two

6 lectures
Flow Control
08:35
For Loops
05:57
While Loops
05:55
Functions
12:45
Scala Programming Exercises
02:33
Scala Programming Exercises - Solutions
15:24

Spark DataFrames with Scala

10 lectures
Quick Note for Windows Users!
00:39
Introduction to Spark DataFrames
06:29
DataFrames Overview
18:12
Spark DataFrame Operations
16:23
GroupBy and Aggregate Functions
10:53
Missing data
13:16
Date and Timestamps
09:53
Quick Note on DataFrame Project
00:11
DataFrame Project Exercises
01:34
DataFrame Project - Solutions
20:20

Introduction to Machine Learning

3 lectures
Introduction to Machine Learning
06:50
Machine Learning with Spark
11:50
IntelliJ IDEA Installation Overview
11:08

Regression with Spark

8 lectures
Introduction to Linear Regression
06:14
Introduction to Regression Section
01:07
Linear Regression Documentation Example
08:29
Alternate Linear Regression Data CSV File
00:17
Linear Regression Walkthrough Part 1
16:40
Linear Regression Walkthrough Part 2
07:26
Linear Regression Exercise Project
02:32
Linear Regression Project Solutions
16:56

Classification with Spark

6 lectures
Introduction to Classification
12:42
Classification Documentation Example
07:39
Spark Classification - Logistic Regression Example - Part 1
15:49
Spark Classification - Logistic Regression Example - Part 2
21:40
Logistic Regression Project Exercise
01:52
Classification Project Solutions
15:16

Model Evaluation

3 lectures
Model Evaluation Overview
10:23
Spark Model Evaluation - Documentation Example
21:32
Spark - Model Evaluation - Regression Example
23:16

Clustering with Spark

6 lectures
Introduction to Clustering with Spark
01:37
KMeans Theory Lecture
05:05
Note on Kmeans
00:08
Example of KMeans with Spark
07:15
Clustering Project Exercise Overview
03:42
Clustering Project Exercises - Solutions
10:31

PCA with Spark

4 lectures
PCA Theory Overview
03:13
PCA with Spark - Documentation Example
06:00
PCA with Spark - Project Exercise
03:06
PCA Spark Exercise - Solutions
10:39

DataBricks and Spark

5 lectures
Databricks Overview
17:24
Introduction to Spark Recommendation Systems
04:03
Spark Recommender System Implementation
13:35
Zeppelin Notebooks on AWS Elastic MapReduce
19:57
So what's next?
00:49

BONUS SECTION: THANK YOU!

1 lectures
Bonus Lecture:
00:10

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