In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.
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.
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.
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.
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.
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.
In this machine learning project, you will develop a machine learning model to accurately forecast inventory demand based on historical sales data.
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 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.