In this project, we are going to work on Deep Learning using H2O to predict Census income.
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.
PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.