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Name: Rajarshi Palit
Type: User
Name: Rajarshi Palit
Type: User
Building a Collaborative Recommendation System (both Used based & Item based) for a store called "Beer Mart", where customers will be recommended the beers that they are most likely to buy.
To create a market mix model for ElecKart (an e-commerce firm from Ontario, Canada) for several products categories - to observe the actual impact of various marketing variables over the past and recommend the optimal budget allocation for different marketing levers for the next year. Built several Linear Regression models like Additive, Multiplicative, Koyck & Distributive Lag to identify the important KPIs that influence the company revenue and their contributions towards the revenue. The main data set is available below:
Clustering Countries based on Socio-Economic Status using K-Means and Hierarchical Clustering process and Dimensionality Reduction with PCA
Example Repo for the Udemy Course "Deployment of Machine Learning Models"
Built several regression models like Linear Regression, Lasso & Ridge Regression, Decision Tree Regression & Random Forest Regression, to predict the overall value of a player. Used Hierarchical Clustering to form clusters of similar players.
Building a regression model using regularization, so as to predict the actual value of the prospective properties with the available independent variables and decide whether to invest in them or not.
Predict if a lead will converted or not and assign lead scores to each of the leads
Analyzing New York Parking Tickets using Spark
This is the repo for the Udemy Course Python Dashboards with Plotly's Dash
Built several classification models like Random Forest, SVM, Decision Trees to predict the telecom churn. Used model selection techniques to finalize on the best model
Repository for the Zero to Deep Learning® Video Course
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