PySpark_ml

This repository includes implementation of following:-

Spark DataFrames
- Spark DataFrame Basics
- Spark DataFrame Operations
- Groupby and Aggregate Functions
- Missing Data
- Dates and Timestamps
Linear Regression
- Linear Regression with PySpark Example (Car Data)
Logistic Regression
- Logistic Regression Example
Tree Methods
- Decision Tree and Random Forest Example
Clustering
- Clustering Example - Iris Dataset
Recommender System
- Recommender Systems and Collaborative Filtering
Natural Language Processing
- Introduction to NLP and Naive Bayes Model with examples
- NLP pipelines
Spark Streaming
- Introduction to Spark Streaming

Name		Name	Last commit message	Last commit date
Latest commit History 29 Commits
Python-and-Spark-for-Big-Data-master		Python-and-Spark-for-Big-Data-master
.gitignore		.gitignore
Linear_Regression.ipynb		Linear_Regression.ipynb
Linear_regression_example.ipynb		Linear_regression_example.ipynb
NLP.ipynb		NLP.ipynb
NLP_example.ipynb		NLP_example.ipynb
README.md		README.md
Spark_Dataframe.ipynb		Spark_Dataframe.ipynb
Spark_dataframe_operations.ipynb		Spark_dataframe_operations.ipynb
Spark_df_groupBy_aggregate.ipynb		Spark_df_groupBy_aggregate.ipynb
Spark_df_timestamp_dates.ipynb		Spark_df_timestamp_dates.ipynb
Spark_missing_values.ipynb		Spark_missing_values.ipynb
Spark_streaming.ipynb		Spark_streaming.ipynb
Tree_methods.ipynb		Tree_methods.ipynb
Tree_methods_example.ipynb		Tree_methods_example.ipynb
k_means.ipynb		k_means.ipynb
k_means_example.ipynb		k_means_example.ipynb
logistic_regression.ipynb		logistic_regression.ipynb
logistic_regression_example.ipynb		logistic_regression_example.ipynb

Provide feedback