Use the Zillow dataset to follow a test-driven approach and build a regression machine learning model to predict the price of the house based on other variables.
In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.
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.
This Elasticsearch example deploys the AWS ELK stack to analyse streaming event data. Tools used include Nifi, PySpark, Elasticsearch, Logstash and Kibana for visualisation.
This project will cover the understanding of Apache Spark with main focus on one of its components, Spark SQL. We will understand how Spark and Spark SQL works, its internal functioning, its capabilities and advantages over other data processing tools. We are going to take up one business problem in the area of Supply Chain. Our tech stack will be Databricks and the latest Spark 3.0 for this project. We will use Spark SQL to understand the business data and generate insights from it which must help us frame a solution for our business problem.
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 deep learning project, you will learn how to build your custom OCR (optical character recognition) from scratch by using Google Tesseract and YOLO to read the text from any images.
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.
