Learn the basics of machine learning on the Spark platform using Apache MLlib.
- [Instructor] Alright, now it's time to take a look…at Machine Learning with Spark.…Machine learning is the way that we can create…repeatable and automated processes…for producing expected output from given data.…This is typically used to find hidden patterns in data…or make predictions.…If we break down machine learning,…there are basically two types.…There are Supervised and Unsupervised.…Supervised learning is when you…train the algorithm to know what the expected output is…and then let it figure out which model,…which statistical model, best produces that output.…
A classic example here is looking at sales forecasts.…Let's say you have the last three years' sales data…by month and you want to predict next year's sales.…What you could do is give Spark…a sample of this data from years past…and ask it to predict the remainder…of the known results you have.…Once it does that, you can then compare…its prediction to what actually happened…to figure out how accurate it was.…Now as I mentioned, this is an automated process.…
- Understanding Spark
- Reviewing Spark components
- Where Spark shines
- Understanding data interfaces
- Working with text files
- Loading CSV data into DataFrames
- Using Spark SQL to analyze data
- Running machine learning algorithms using MLib
- Querying streaming data
- Connecting BI tools to Spark
Skill Level Intermediate
1. Introducing Apache Spark
2. Analyzing Data in Spark
3. Using Spark SQL to Analyze Data
4. Running Machine Learning Algorithms Using MLlib
5. Real-Time Data Analysis with Spark Streaming
6. Connecting BI Tools to Spark
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