Build Apache Spark Machine Learning and Analytics Projects (Total 5 Projects) on Databricks Environment
Instructors: Bigdata Engineer
Why this course?
Build Apache Spark Machine Learning and Analytics Projects (Total 5 Projects) on Databricks Environment useful for Bigdata Engineers
Learn the latest Big Data Technology Tool- Apache Superset! And learn to use it with one of the most popular way!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Superset! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Apache Superset to solve their big data problems!
Master Machine Learning Project Building with Apache Spark.
Real-time Prediction of online shoppers’ purchasing intention Project using Apache Spark Machine Learning Models a Data Pipeline Creation.
What is this course about?
This course covers all the fundamentals about Apache Spark Machine Learning Project with Scala and teaches you everything you need to know about developing Spark Machine Learning applications using Scala, the Machine Learning Library API for Spark. At the end of this course, you will gain in-depth knowledge about Spark Machine Learning and general big data manipulation skills to help your company to adapt Spark Machine Learning for building Machine Learning Model processing pipelines and data analytics applications. This course will be absolutely critical to anyone trying to make it in data science today.
1 Project Details:
This project is about an eCommerce company that sells clothes online.
This project is about customers who buy clothes online.
The store offers in-store style and clothing advice sessions.
Customers come into the store, have sessions/meetings with a personal stylist, then they can go home and order either on a mobile app or website for the clothes they want.
We need to predict the future spending of Customer(ie Revenue for Company ) so business strategies can be made to convert "Customer" to "Loyalty Customer"
In this Data Science Machine Learning project, we will create an eCommerce Customer Revenue Prediction Project using Apache Spark Machine Learning Models using Linear Regression, one of the predictive models.
eCommerce Customer Revenue Prediction Project a Real-time Use Case on Apache Spark
2 Project Details:
Telemarketing advertising campaigns are a billion-dollar effort and one of the central uses of the machine learning model. However, its data and methods are usually kept under lock and key. The Project is related to the direct marketing campaigns of a banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed.
In this Data Science Machine Learning project, we will create Predicting Customer Response to Bank Direct Telemarketing Campaign Project in Apache Spark Project (Machine Learning) using Classification Model, Logistic Regression, few of the predictive models.
Predicting Customer Response to Bank Direct Telemarketing Campaign Project a Real-time Use Case on Apache Spark
3 Project Details:
Once a user logs into an online shopping website, knowing whether the person will make a purchase or not holds a massive economical value. A lot of current research is focused on real-time revenue predictors for these shopping websites. In this article, we will start building a revenue predictor for one such website.
In this Data Science Machine Learning project, we will create a Real-time prediction of online shoppers’ purchasing intention Project using Apache Spark Machine Learning Models using Logistic Regression, one of the predictive models a data pipeline project
Prediction of Online Shoppers’ Purchasing Intention Project a Real-time Use Case on Apache Spark
4 Project Details:
The goal of this project is to provide hands-on training that applies directly to real-world Big Data projects. It uses the learn-train-practice-apply methodology where you
Taught by an expert in the field, you will also get a prompt response to your queries and excellent support from Udemy.
In this course, you will learn to Analyze data (Apache Web Server log) in Apache Spark using Databricks Notebook (Community edition),
5 Project Details:
This course attempts to explain the basic concepts of the exponential family of predict modeling. You shall learn about the different components of this family and their relationship. Also, learn about how to identify the right model fitment to the given data series.
One of the most common mistakes an analyst could make during a predictive modeling project is ignorance of sample bias in their data. The cost of making such a mistake can be quite substantial to an organization's business outcome.
In this video course, we will share with you some secrets on how to avoid this mistake. You will learn the following topics:
1) Classification Model
2) Regression Model
Learn the fundamentals of predictive analysis through an easy to understand conceptual course.
At the end of the class, you should have gained sufficient knowledge to help you detect and reduce sample bias in future predictive modeling or advanced analytics projects.
Predictive Analytics with Apache Spark using Databricks (Unofficial) Notebook (Community edition) including Project
Databricks lets you start writing Spark ML code instantly so you can focus on your data problems.
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