UNLV_Procject

In University of Nevada, Las Vegas
Period: 2023.06.25 ~ 2023.07.23
Project: Definition of scaleable machine learning for big data
Description: Big data analytics provides scalable solutions for distributed or very large data. For this project, students will have hands-on experience installing Apache Spark, and practicing python libraries, e.g., MLLib, while applying supervised and unsupervised machine learning algorithms to large datasets for data analysis and developing machine learning models.

Project subject

how to implement map and reduce function using Spark

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
__pycache__		__pycache__
Machine Learning for Big Data.pptx		Machine Learning for Big Data.pptx
README.md		README.md
Research Presentation [Shelby's class ].pdf		Research Presentation [Shelby's class ].pdf
Research Presentation [final Presentation].pdf		Research Presentation [final Presentation].pdf
Research Presentation [final Presentation].pptx		Research Presentation [final Presentation].pptx
SparkIntro.ipynb		SparkIntro.ipynb
Training_Data.csv		Training_Data.csv
UNLV_Project-main.zip		UNLV_Project-main.zip
Week2(mon)-session.pdf		Week2(mon)-session.pdf
Week2(mon)-session.pptx		Week2(mon)-session.pptx
[2023.06.29] KNN.ipynb		[2023.06.29] KNN.ipynb
code2.ipynb		code2.ipynb
mapreduce_f.py		mapreduce_f.py
mapreduce_main.py		mapreduce_main.py
mapreduce_ml.py		mapreduce_ml.py
mapreduce_spark2_sample.py		mapreduce_spark2_sample.py
mapreduce_spark_train.py		mapreduce_spark_train.py
sklearn_ml.py		sklearn_ml.py
spark_ml.py		spark_ml.py
train.csv		train.csv