ProjectPro

SEPTEMBER 27, 2021

When working with datasets of different types to implement data science algorithms, one has to understand the datasets properly. Exploring the independent variables in the dataset gives a fair idea about what algorithms can be used for that dataset. Two such popular tools are correlation and covariance.

Datasets 52

Datasets Finance Portfolio Banking 52

ProjectPro

NOVEMBER 10, 2016

The job role of a Hadoop developer is playing with large datasets to program big data applications and anybody capable of doing it is the right fit for employers regardless of the experience. There are at least 16% hadoopers with Python and 6% hadoopers with R programming expertise.

Hadoop 52

Hadoop NoSQL Java Electronics 52

ProjectPro

NOVEMBER 30, 2021

Project Idea: In this project, you will work on a retail store’s data and learn how to realize the association between different products. Additionally, you will learn how to implement Apriori and Fpgrowth algorithms over the given dataset. The goal is to predict the sales and revenue of different stores based on historical data.

Business Analyst 52

Business Analyst Project Retail Datasets 52

ProjectPro

AUGUST 11, 2016

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

ProjectPro

JUNE 17, 2015

“Companies are betting big that harnessing data can play a major role in their competitive plans and is leading to high pay for critical skills.”-said The big data phenomenon is just incomplete without the use of popular NoSQL databases like MongoDB, Cassandra, HBase Neo4j, CouchDB, Riak and Redis. from the previous year.

Cloud Computing 40

Cloud Computing Big Data R (Programming) Big Data Skills 40

ProjectPro

DECEMBER 22, 2016

Data Analyst Interview Questions and Answers 1) What is the difference between Data Mining and Data Analysis? Data Mining vs Data Analysis Data Mining Data Analysis Data mining usually does not require any hypothesis. Data analysis begins with a question or an assumption.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

Knowledge Hut

FEBRUARY 7, 2023

A data science platform is software that includes a variety of technologies for machine learning, data science, and other advanced analytics projects. Typically, data science projects involve using an abundance of ls (eg. GUI Dashboards They have integrated dashboards to help visualize the graphs and results for the clients.

Data Science 52

Data Science Google Cloud Programming Language AWS 52