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.
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
In this project, we are going to talk about H2O and functionality in terms of building Machine Learning models.
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.
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.
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.