This is a machine learning repository for beginner in machine learning. here it contain various examples, papers, implemented algorithms and usecase documents.
in future i will more and more link papers and document related to new learning. your feedback is appreciated
Hypothesis testing explanation follow medium article - https://medium.com/@yugagrawal95/hypothesis-testing-in-machine-learning-using-python-a0dc89e169ce
K-means clustering using seaborn visualization check - https://www.kaggle.com/yugagrawal95/k-means-clustering-using-seaborn-visualization
RFM Analysis using Python - https://www.kaggle.com/yugagrawal95/rfm-analysis
Market Basket Analysis using Apriori - https://www.kaggle.com/yugagrawal95/market-basket-analysis-apriori-in-python
Product Recommendation using collaborative filtering - using User-User and Item-Item approach. https://www.kaggle.com/yugagrawal95/collaborative-filtering
Scale machine learning using pyspark on titanic dataset using pipeline - https://github.com/yug95/MachineLearning/tree/master/Spark-ml
Deploy scale model built in pyspark using Flask webapp - https://github.com/yug95/MachineLearning/tree/master/flask_app_deployment