Edureka

APRIL 17, 2023

In today’s data-driven world, data analytics plays a critical role in helping businesses make informed decisions. As a data analytics professional, building a strong portfolio of projects is essential to showcase your skills and expertise to potential employers. What is the Role of Data Analytics?

Portfolio 40

Portfolio Data Analytics Project Data Mining 40

Knowledge Hut

NOVEMBER 27, 2023

Understanding what defines data in the modern world is the first step toward the Data Science self-learning path. There is a much broader spectrum of things out there which can be classified as data. How would one know what to sell and to which customers, based on data? This is where Data Science comes into the picture.

Data Science 97

Data Science Healthcare Machine Learning Telecommunication 97

Knowledge Hut

APRIL 23, 2024

Big Data Use Cases in Industries You can go through this section and explore big data applications across multiple industries. Clinical Decision Support: By analyzing vast amounts of patient data and offering in-the-moment insights and suggestions, use cases for big data in healthcare helps workers make well-informed judgments.

Big Data 52

Big Data Retail Recruitment Transportation 52

Knowledge Hut

OCTOBER 27, 2023

No matter if you're just a beginner, intermediate, or advanced Power BI user, you can build up your portfolio by doing these projects. Power BI projects cover a wide range of industries and data analysis scenarios, allowing you to gain experience in different contexts. Grab info from a website using good APIs.

BI 52

BI Project Datasets Healthcare 52

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. To build such ML projects, you must know different approaches to cleaning raw data. To develop such algorithms, you need to have a thorough understanding of the following: a.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

OCTOBER 27, 2021

The huge volumes of financial data have helped the finance industry streamline processes, reduce investment risks, and optimize investment portfolios for clients and companies. There is a wide range of open-source machine learning algorithms and tools that fit exceptionally with financial data. Our data is imbalanced.

Finance 52

Finance Machine Learning Project Banking 52

ProjectPro

FEBRUARY 8, 2016

The main techniques used here are data mining and data aggregation. Descriptive analytics involves using descriptive statistics such as arithmetic operations on existing data. These operations make raw data understandable to investors, shareholders, and managers.

Data Mining 56

Data Mining Big Data Medical Healthcare 56