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Data Science Projects in Retail & Ecommerce

Deploying Machine Learning Models with Flask for Beginners

In this MLOps on GCP project you will learn to deploy a sales forecasting ML Model using Flask.

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Machine Learning project for Retail Price Optimization

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.

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Recommender System Machine Learning Project for Beginners-2

Recommender System Machine Learning Project for Beginners Part 2- Learn how to build a recommender system for market basket analysis using association rule mining.

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Recommender System Machine Learning Project for Beginners-1

Recommender System Machine Learning Project for Beginners - Learn how to design, implement and train a rule-based recommender system in Python

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Build Customer Propensity to Purchase Model in Python

In this machine learning project, you will learn to build a machine learning model to estimate customer propensity to purchase.

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Walmart Sales Forecasting Data Science Project

Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.

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Machine Learning Project to Forecast Rossmann Store Sales

In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.

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Avocado Machine Learning Project Python for Price Prediction

In this ML Project, you will use the Avocado dataset to build a machine learning model to predict the average price of avocado which is continuous in nature based on region and varieties of avocado.

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Ecommerce product reviews - Pairwise ranking and sentiment analysis

This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

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Customer Churn Prediction Analysis using Ensemble Techniques

In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.

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Customer Market Basket Analysis using Apriori and Fpgrowth algorithms

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.

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Time Series Python Project using Greykite and Neural Prophet

In this time series project, you will forecast Walmart sales over time using the powerful, fast, and flexible time series forecasting library Greykite that helps automate time series problems.

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Create Your First Chatbot with RASA NLU Model and Python

Learn the basic aspects of chatbot development and open source conversational AI RASA to create a simple AI powered chatbot on your own.

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PyCaret Project to Build and Deploy an ML App using Streamlit

In this PyCaret Project, you will build a customer segmentation model with PyCaret and deploy the machine learning application using Streamlit.

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Build a Multi Touch Attribution Machine Learning Model in Python

Identifying the ROI on marketing campaigns is an essential KPI for any business. In this ML project, you will learn to build a Multi Touch Attribution Model in Python to identify the ROI of various marketing efforts and their impact on conversions or sales..

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ML Model Deployment on AWS for Customer Churn Prediction

MLOps Project-Deploy Machine Learning Model to Production Python on AWS for Customer Churn Prediction

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Recommender System Machine Learning Project for Beginners-3

Content Based Recommender System Project - Building a Content-Based Product Recommender App with Streamlit

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Build a Graph Based Recommendation System in Python -Part 1

Python Recommender Systems Project - Learn to build a graph based recommendation system in eCommerce to recommend products.

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Recommender System Machine Learning Project for Beginners-4

Collaborative Filtering Recommender System Project - Comparison of different model based and memory based methods to build recommendation system using collaborative filtering.

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Build a Review Classification Model using Gated Recurrent Unit

In this Machine Learning project, you will build a classification model in python to classify the reviews of an app on a scale of 1 to 5 using Gated Recurrent Unit.

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Build a Hybrid Recommender System in Python using LightFM

In this Recommender System project, you will build a hybrid recommender system in Python using LightFM .

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PyTorch Project to Build a LSTM Text Classification Model

In this PyTorch Project you will learn how to build an LSTM Text Classification model for Classifying the Reviews of an App .

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Build a Graph Based Recommendation System in Python-Part 2

In this Graph Based Recommender System Project, you will build a recommender system project for eCommerce platforms and learn to use FAISS for efficient similarity search.

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BigMart Sales Prediction ML Project in Python

The goal of the BigMart Sales Prediction ML project is to build and evaluate different predictive models and determine the sales of each product at a store.

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Inventory Demand Forecasting using Machine Learning in R

In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.

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Identifying Product Bundles from Sales Data Using R Language

In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.

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Machine learning for Retail Price Recommendation with R

Use the Mercari Dataset with dynamic pricing to build a price recommendation algorithm using machine learning in R to automatically suggest the right product prices.

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Data Science Project - Instacart Market Basket Analysis

Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.

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Graduate Research assistance at Stony Brook University

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Graduate Student at Northwestern University

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Data Science Intern, Capgemini

I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills in Data Engineering/Science and hoping to find real-world projects fortunately, I came across Project Pro. Project Pro helped me by providing an in-depth explanation of the end-to-end real-world data engineering projects. From data extraction, transformation, and storage up to data visualization. I learned more about Kafka, AWS, NI-FI, and Spark. Thru the help of the knowledge I gained from Project Pro, I was able to do well in the coding exams, interview and helped me land a job at EY. I will recommend every aspiring data professional as well as existing data science/engineer expert to try Project Pro to enhance their knowledge.

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Director Data Analytics at EY / EY Tech

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Data Consultant at Confidential

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ETL (Abintio) developer at IBM

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Tech Leader | Stanford / Yale University