Reserve a bit of your time to learn some real-world skills. If you’re a beginner Apache Spark engineer, machine learning engineer, or someone somehow dealing with Big data, it’s your chance to improve your skills and knowledge. We’re going to create a house sale price prediction project using Apache Spark machine learning libraries and Databricks platform. If you have machine learning, SQL, and Apache Spark basics – that’s great. Let’s waste no more time and work on improving your skill set!
The growing number of more diverse and more user-focused data products creates a high demand for machine learning specialists — the ones who can develop personalizations, recommendations, and make predictive insights. Data scientists can choose some great tools. But some of the traditional ones require more time for supporting the infrastructure than building the models to solve real problems. That’s because the volumes and variety of data gathered by organizations have been increasing non-stop.
This Spark tutorial will introduce you to a tool that is designed for simplicity, scalability, and easy integration with other tools. Using Spark ML libraries, you can solve data problems faster and handle a greater workload of distributed data engineering. Mastering the Apache Spark machine learning tool is desired in many different positions, such as data analyst, data scientist/engineer, AI scientist, database engineer, software engineer, and more. Experienced ones make and will continue to make solid incomes from that.
The end ‘product’ of your decision to enroll in this course will be implementing a Spark ML project for house price prediction. You’ll learn to use a machine learning model and generate some output in the form of a prediction.
To achieve the above goals, here’s what you’ll cover in the lessons:
You’re going to do hands-on learning to implement a Spark ML project for house sale price prediction. I’ll explain all the necessary concepts and more, and you’ll have to do some work on your own.
To start this practical course, you don’t need any additional investments in your system. Make sure you’re using a fully functional non-beta version of one of the popular web browsers. There’s downloadable material available before you hit to play the first lecture. Join the course and leave with a tangible result to add to your profile. See you inside the Apache Spark machine learning course!
Course consist of total 1h 28min of content, in total.
I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes
My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.
- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments