Pandas are not an endangered species when gulped by Python.
I like pandas, lets build pipelines and regress trees.
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Simplify Data Solutions
- Toronto, ON
- www.linkedin.com/in/atifzafar
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Customer-Segments-Arvato
Customer-Segments-Arvato PublicAnalyze customers using unsupervised learning, PCA and K-Mean Clustering of Arvato dataset
HTML 2
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Disaster-Response-with-Figure-Eight
Disaster-Response-with-Figure-Eight PublicApply Data Engineering to Build ETL & NLP Machine Learning Pipelines and Create an App for Disaster Relief using Flask
Jupyter Notebook 1
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Recommendation-with-IBM
Recommendation-with-IBM PublicMake a recommendation engine using ranked based, user-user based collaborative filtering, content based, and matrix factorization
HTML 1
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Sparkify-with-Apache-Spark-Mllib-Data-Science
Sparkify-with-Apache-Spark-Mllib-Data-Science PublicManipulate large and realistic datasets with Spark to engineer relevant features for predicting churn. Use Spark MLlib to build machine learning models with large datasets.
Jupyter Notebook 1
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Cloud-Data-Warehouse-with-Redshift-AWS
Cloud-Data-Warehouse-with-Redshift-AWS PublicCloud Data Warehouse of Sparkify Data using Redshift
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Spark-ETL-DataLake
Spark-ETL-DataLake PublicEMR - Spark ETL of JSON Data Lake to Parquet DL for DWH
Python 1
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