Udemy - Spark and Python for Big Data with PySpark
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size1.6 GB
- Uploaded ByLMorningStar
- Downloads157
- Last checkedJan. 20th '20
- Date uploadedJan. 18th '20
- Seeders 6
- Leechers3
Spark and Python for Big Data with PySpark
Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!
What you’ll learn?
Use Python and Spark together to analyze Big Data
Learn how to use the new Spark 2.0 DataFrame Syntax
Work on Consulting Projects that mimic real world situations!
Classify Customer Churn with Logisitic Regression
Use Spark with Random Forests for Classification
Learn how to use Spark’s Gradient Boosted Trees
Use Spark’s MLlib to create Powerful Machine Learning Models
Created by Jose Portilla
Last updated 9/2019
English
English [Auto-generated], French [Auto-generated]
For More Updated Udemy Course: FreeAllCourse.Com
Files:
[FreeAllCourse.Com] Udemy - Spark and Python for Big Data with PySpark 1. Introduction to Course- 1. Introduction.mp4 (11.6 MB)
- 1. Introduction.srt (4.5 KB)
- 2. Course Overview.mp4 (14.4 MB)
- 2. Course Overview.srt (14.7 KB)
- 2.1 Course Overview Slides.html (0.2 KB)
- 2.2 Python-and-Spark-for-Big-Data-master.zip.zip (1.7 MB)
- 3. Frequently Asked Questions.html (0.4 KB)
- 3.1 Python-and-Spark-for-Big-Data-master.zip.zip (1.7 MB)
- 4. What is Spark Why Python.mp4 (48.1 MB)
- 4. What is Spark Why Python.srt (30.5 KB)
- 4.1 Spark and Python Slides.html (0.2 KB)
- 1. Introduction to Machine Learning and ISLR.mp4 (18.9 MB)
- 1. Introduction to Machine Learning and ISLR.srt (17.6 KB)
- 1.1 Slides for ML Intro.html (0.2 KB)
- 2. Machine Learning with Spark and Python with MLlib.mp4 (51.3 MB)
- 2. Machine Learning with Spark and Python with MLlib.srt (15.8 KB)
- 1. Linear Regression Theory and Reading.mp4 (9.9 MB)
- 1. Linear Regression Theory and Reading.srt (8.1 KB)
- 1.1 Slides for Linear Regression.html (0.2 KB)
- 2. Linear Regression Documentation Example.mp4 (40.6 MB)
- 2. Linear Regression Documentation Example.srt (21.9 KB)
- 3. Regression Evaluation.mp4 (12.0 MB)
- 3. Regression Evaluation.srt (10.8 KB)
- 4. Linear Regression Example Code Along.mp4 (39.2 MB)
- 4. Linear Regression Example Code Along.srt (23.3 KB)
- 4.1 Ecommerce_Customers.csv.csv (84.8 KB)
- 5. Linear Regression Consulting Project.mp4 (6.8 MB)
- 5. Linear Regression Consulting Project.srt (4.9 KB)
- 6. Linear Regression Consulting Project Solutions.mp4 (38.8 MB)
- 6. Linear Regression Consulting Project Solutions.srt (22.7 KB)
- 1. Logistic Regression Theory and Reading.mp4 (20.6 MB)
- 1. Logistic Regression Theory and Reading.srt (17.9 KB)
- 1.1 Slides for Logistic Regression.html (0.2 KB)
- 2. Logistic Regression Example Code Along.mp4 (53.4 MB)
- 2. Logistic Regression Example Code Along.srt (23.5 KB)
- 3. Logistic Regression Code Along.mp4 (41.5 MB)
- 3. Logistic Regression Code Along.srt (27.3 KB)
- 3.1 Explanation of AUC.html (0.1 KB)
- 3.2 Great Example from Databricks.html (0.1 KB)
- 4. Logistic Regression Consulting Project.mp4 (6.3 MB)
- 4. Logistic Regression Consulting Project.srt (5.3 KB)
- 5. Logistic Regression Consulting Project Solutions.mp4 (34.0 MB)
- 5. Logistic Regression Consulting Project Solutions.srt (15.2 KB)
- 1. Tree Methods Theory and Reading.mp4 (14.7 MB)
- 1. Tree Methods Theory and Reading.srt (11.7 KB)
- 1.1 Slides for Tree Methods.html (0.2 KB)
- 2. Tree Methods Documentation Examples.mp4 (34.2 MB)
- 2. Tree Methods Documentation Examples.srt (20.7 KB)
- 3. Decision Tress and Random Forest Code Along Examples.mp4 (49.1 MB)
- 3. Decision Tress and Random Forest Code Along Examples.srt (30.8 KB)
- 4. Random Forest - Classification Consulting Project.mp4 (5.4 MB)
- 4. Random Forest - Classification Consulting Project.srt (3.8 KB)
- 5. Random Forest Classification Consulting Project Solutions.mp4 (15.9 MB)
- 5. Random Forest Classification Consulting Project Solutions.srt (11.8 KB)
- 1. K-means Clustering Theory and Reading.mp4 (12.9 MB)
- 1. K-means Clustering Theory and Reading.srt (10.7 KB)
- 1.1 Slides for Clustering.html (0.2 KB)
- 2. KMeans Clustering Documentation Example.mp4 (20.9 MB)
- 2. KMeans Clustering Documentation Example.srt (14.7 KB)
- 3. Clustering Example Code Along.mp4 (27.9 MB)
- 3. Clustering Example Code Along.srt (18.5 KB)
- 4. Clustering Consulting Project.mp4 (6.6 MB)
- 4. Clustering Consulting Project.srt (4.7 KB)
- 5. Clustering Consulting Project Solutions.mp4 (23.0 MB)
- 5. Clustering Consulting Project Solutions.srt (11.5 KB)
- 1. Introduction to Recommender Systems.mp4 (12.7 MB)
- 1. Introduction to Recommender Systems.srt (10.0 KB)
- 1.1 Recommender Slides.html (0.2 KB)
- 2. Recommender System - Code Along Project.mp4 (24.6 MB)
- 2. Recommender System - Code Along Project.srt (18.0 KB)
- 1. Introduction to Natural Language Processing.mp4 (14.3 MB)
- 1. Introduction to Natural Language Processing.srt (13.2 KB)
- 1.1 NLP Slides.html (0.2 KB)
- 2. NLP Tools Part One.mp4 (36.2 MB)
- 2. NLP Tools Part One.srt (22.9 KB)
- 3. NLP Tools Part Two.mp4 (18.9 MB)
- 3. NLP Tools Part Two.srt (10.7 KB)
- 4. Natural Language Processing Code Along Project.mp4 (35.2 MB)
- 4. Natural Language Processing Code Along Project.srt (19.6 KB)
- 1. Introduction to Streaming with Spark!.mp4 (32.6 MB)
- 1. Introduction to Streaming with Spark!.srt (17.5 KB)
- 1.1 Spark Streaming Slides.html (0.2 KB)
- 2. Spark Streaming Documentation Example.mp4 (28.6 MB)
- 2. Spark Streaming Documentation Example.srt (17.4 KB)
- 3. Spark Streaming Twitter Project - Part.mp4 (11.8 MB)
- 3. Spark Streaming Twitter Project - Part.srt (7.3 KB)
- 4. Spark Streaming Twitter Project - Part Two.mp4 (29.3 MB)
- 4. Spark Streaming Twitter Project - Part Two.srt (18.2 KB)
- 5. Spark Streaming Twitter Project - Part Three.mp4 (55.0 MB)
- 5. Spark Streaming Twitter Project - Part Three.srt (29.3 KB)
- 1. Bonus Lecture.html (0.5 KB)
- 1. Set-up Overview.mp4 (10.8 MB)
- 1. Set-up Overview.srt (10.2 KB)
- 1.1 Slides for Installation Options Overview.html (0.2 KB)
- 1.2 Slides for Installation.html (0.2 KB) <
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