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Big Data Analytics with Apache Spark and Python
Apache Spark programming with Python, Spark SQL, Spark Streaming, Machine Learning and Real time Data Science
Год выпуска: 2016
Производитель: Udemy / V2 Maestros
Сайт производителя: udemy.com/big-data-analytics-with-apache-spark-and-python
Автор: Oscar Kalipe
Продолжительность: 9:30
Тип раздаваемого материала: Видеоклипы
Язык: Английский
Описание: Apache Spark is the most active Apache project, and it is pushing back Map Reduce. It is fast, general purpose and supports multiple programming languages, data sources and management systems. More and more organizations are adapting Apache Spark to build big data solutions through batch, interactive and stream processing paradigms. The demand for trained professionals in Spark is going through the roof. Being a new technology, there aren't enough training sources to provide easy guidance on building end-to-end solutions.

Содержание

Section 1: Introduction
Lecture 1
About the course
08:42
Lecture 2
About V2 Maestros
01:39
Lecture 3
Resource Bundle
Article
Section 2: Overview
Lecture 4
Hadoop Overview
10:06
Lecture 5
HDFS Architecture
14:46
Lecture 6
Map Reduce - How it works
17:24
Lecture 7
Map Reduce - Example
16:46
Lecture 8
Hadoop Stack
06:27
Lecture 9
What is Spark?
14:03
Lecture 10
Spark Architecture - Part 1
13:23
Lecture 11
Spark Architecture - Part 2
13:25
Lecture 12
Installing Spark and Setting up for Python
12:05
Quiz 1
Hadoop and Spark Architecture
5 questions
Section 3: Programming with Spark
Lecture 13
Spark Transformations
11:33
Lecture 14
Spark Actions
15:04
Lecture 15
Advanced Spark Programming
10:10
Lecture 16
Python - Spark Programming examples 1
16:11
Lecture 17
Python - Spark Programming Examples 2
17:18
Quiz 2
Data Engineering with Spark
5 questions
Lecture 18
PRACTICE Exercise : Spark Operations
Article
Section 4: Spark SQL
Lecture 19
Spark SQL Overview
10:03
Lecture 20
Python - Spark SQL Examples
16:16
Quiz 3
Spark SQL
2 questions
Lecture 21
PRACTICE Exercise : Spark SQL
Article
Section 5: Spark Streaming
Lecture 22
Streaming with Apache Spark
15:53
Lecture 23
Python - Spark Streaming examples
17:47
Quiz 4
Spark Streaming
3 questions
Section 6: Real time Data Science
Lecture 24
Basic Elements of Data Science
11:51
Lecture 25
The Dataset
10:44
Lecture 26
Learning from relationships
12:55
Lecture 27
Modeling and Prediction
09:31
Lecture 28
Data Science Use Cases
07:47
Lecture 29
Types of Analytics
12:08
Lecture 30
Types of Learning
17:16
Lecture 31
Doing Data Science in real time with Spark
07:39
Quiz 5
Spark Data Science
5 questions
Section 7: Machine Learning with Spark
Lecture 32
Spark Machine Learning
12:18
Lecture 33
Analyzing Results and Errors
13:46
Lecture 34
Linear Regression
19:00
Lecture 35
Spark Use Case : Linear Regression
18:33
Lecture 36
Decision Trees
10:42
Lecture 37
Spark Use Case : Decision Trees Classification
14:58
Lecture 38
Principal Component Analysis
07:28
Lecture 39
Random Forests Classification
10:31
Lecture 40
Python Use Case : Random Forests & PCA
13:16
Lecture 41
Text Preprocessing with TF-IDF
14:53
Lecture 42
Naive Bayes Classification
19:21
Lecture 43
Spark Use Case : Naive Bayes & TF-IDF
07:26
Lecture 44
K-Means Clustering
11:53
Lecture 45
Spark Use Case : K-Means
14:26
Lecture 46
Recommendation Engines
11:55
Lecture 47
Spark Use Case : Collaborative Filtering
06:34
Lecture 48
Real Time Twitter Data Sentiment Analysis
10:11
Quiz 6
Spark Machine Learning Algorithms
4 questions
Lecture 49
PRACTICE Exercise : Spark Clustering
Article
Lecture 50
PRACTICE Exercise : Spark Classification
Article
Section 8: Conclusion
Lecture 51
Closing Remarks
01:56
Lecture 52
BONUS Lecture : Other courses you should check out
Article
Файлы примеров: отсутствуют
Формат видео: MP4
Видео: AVC, 1280x720, 16:9, 30fps, 182kbps
Аудио: AAC, 44.1kHz, 64kbps, stereo

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