There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.
Data science project in R to develop automated methods for predicting the cost and severity of insurance claims.
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.
Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.
In this project, we are going to work on Sequence to Sequence Prediction using IMDB Movie Review Dataset using Keras in Python.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.
In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.
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.