Knowledge Hut

JANUARY 25, 2024

In the context of data science , clean data is crucial because the quality of your data directly impacts the reliability of your analysis and the outcomes of your algorithms. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making.

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

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

ProjectPro

AUGUST 24, 2021

Source Code: Analyse Movie Ratings Data Unlock the ProjectPro Learning Experience for FREE 11) Retail Analytics Project Example For retail stores , inventory levels, supply chain movement, customer demand, sales, etc. There are three stages in this real-world data engineering project. The second stage is data preparation.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52