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 spark project, you will use the real-world production logs from NASA Kennedy Space Center WWW server in Florida to perform scalable log analytics with Apache Spark, Python, and Kafka.
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.
The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.
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.
Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
