Knowledge Hut

JANUARY 25, 2024

What is Data Cleaning? Data cleaning, also known as data cleansing, is the essential process of identifying and rectifying errors, inaccuracies, inconsistencies, and imperfections in a dataset. It involves removing or correcting incorrect, corrupted, improperly formatted, duplicate, or incomplete data.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

ProjectPro

JANUARY 24, 2023

They were able to use SageMaker's pre-built algorithms and libraries to quickly and easily train their ML models and then deploy them to the edge (i.e., SageMaker also supports building customized algorithms and frameworks and allows for flexible distributed training options.

Building 52

Building Algorithm Machine Learning AWS 52

Knowledge Hut

DECEMBER 26, 2023

With the help of the company's "augmented analytics," you can ask natural-language inquiries and receive informative responses while also applying thoughtful data preparation. Some of the best features of oracle analytics cloud are augmented analytics, data discovery, and natural language processing.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

DECEMBER 22, 2016

Data analysis involves data cleaning. Results of data mining are not always easy to interpret. Data analysts interpret the results and convey the to the stakeholders. Data mining algorithms automatically develop equations. Data analysts have to develop their own equations based on the hypothesis.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52