GitHub - desaiankitb/spark-mllib: Apache Spark is one of the most widely used and supported open-source tools for machine learning and big data. In this repo, discover how to work with this powerful platform for machine learning. This repo discusses MLlib—the Spark machine learning library—which provides tools for data scientists and analysts who would rather find solutions to business problems than code, test, and maintain their own machine learning libraries. Repo shows how to use DataFrames to organize data structure, and covers data preparation and the most commonly used types of machine learning algorithms: clustering, classification, regression, and recommendations. You will have experience loading data into Spark, preprocessing data as needed to apply MLlib algorithms, and applying those algorithms to a variety of machine learning problems.

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Apache Spark is one of the most widely used and supported open-source tools for machine learning and big data. In this repo, discover how to work with this powerful platform for machine learning. This repo discusses MLlib—the Spark machine learning library—which provides tools for data scientists and analysts who would rather find solutions to b…

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Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
01_normalize_data.py		01_normalize_data.py
02_standardize_data.py		02_standardize_data.py
03_bucketize_data.py		03_bucketize_data.py
04_tokenize_data.py		04_tokenize_data.py
05_TFIDF_data.py		05_TFIDF_data.py
06_kmeans.py		06_kmeans.py
07_bkmeans.py		07_bkmeans.py
08_preprocess_classification.py		08_preprocess_classification.py
09_NaiveBayes_classification.py		09_NaiveBayes_classification.py
10_MLP_classification.py		10_MLP_classification.py
11_DecisionTree_classification.py		11_DecisionTree_classification.py
12_linearRegression.py		12_linearRegression.py
13_decisionTreeRegression.py		13_decisionTreeRegression.py
14_gbTreeRegression.py		14_gbTreeRegression.py
clustering_dataset.csv		clustering_dataset.csv
employee.txt		employee.txt
iris.data		iris.data
power-plant.csv		power-plant.csv