MapReduce is Framework as well as a paradigm of computing. By the way of map-reduce, we are able to break-down complex computation into distributed computing.
As part of this chapter, we are going to learning how to build MapReduce programmes using Java.
Please make sure you work along with the course instead of just sitting back and watching.
Happy Learning!
Spark Streaming is an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant processing of live data streams. Learn Spark Streaming from the industry experts.
Learn to load and save data using Spark, compression, and how to handle various file formats using Spark from the industry experts.
Whenever you make a request to a web server for a page, it records it in a file which is called logs.
The logs of a webserver are the gold mines for gaining insights in the user behaviour. Every data scientists usually look at the logs first to understand the behaviour of the users. But since the logs are humongous in size, it takes a distributed framework like Hadoop or Spark to process it.
As part of this project, you will learn to parse the text data stored in logs of a web server using the Apache Spark.
This SQL Tutorial course helps people in learning the basics of SQL and RDBMS through hands-on on MySQL database.
A gentle introduction to the world of Machine Learning. Know about the various types of Machine Learning, and their various applications.
Welcome to this project on the Forecasting Bike Rentals with DecisionTreeRegressor, LinearRegression, RandomForestRegressor using scikit-learn. In this project, you will use Python and scikit-learn to build models using the above-mentioned algorithms, and apply them to forecast the bike rentals.
Forecasting is a regression problem, which is a highly demanded skill in the real world. This exercise enables you to understand the basic workflow to solve a regression problem, which includes data preprocessing and data modeling steps. You will understand how Pandas and scikit-learn, in association with Python, could be used to solve a machine learning problem end-to-end project. In addition …
Welcome to this project on Classify Clothes from Fashion MNIST Dataset with a couple of Machine Learning algorithms like SGD Classifier, XGBClassifier, Softmax Regression (multi-class LogisticRegression), DecisionTreeClassifier, RandomForestClassifier, Ensemble (with soft voting) using scikit-learn. In this project, you will use Python and scikit-learn to build Machine Learning models, and apply them to predict the class of clothes from Fashion MNIST Dataset.
In this end-to-end Machine Learning project, you will get a hands-on overview of how to methodologically solve a machine learning classification problem. As a part of it, you will understand various methods of improvising the models using hyperparameter tuning …
This chapter covers different Pandas constructs and functions which are normally used in Machine Learning projects
