Let’s watch the next video as our SME, Ajay, explains the key takeaways from this module.
So, in this session, you learnt about various machine learning algorithms and their implementation using PySpark. The following topics and concepts were covered in this module:
- Basic EDA using Spark ML Library: This included an overview of Spark ML library, imputer, vector assembler and pipeline.
- Linear Regression: You first learnt about linear regression and the basic model building techniques, and then the implementation of linear regression.
- Logistic Regression: In this session, you learnt the basics of logistic regression and then implemented the CTR prediction model using the logistic regression algorithm.
- K-Means Clustering: In this session, you learnt the basics of clustering and implemented K-Means Clustering on the music industry data set.
Please find the lecture notes of the module attached below.
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