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

AltexSoft

FEBRUARY 21, 2023

This blog post will delve into the challenges, approaches, and algorithms involved in hotel price prediction. Hotel price prediction is the process of using machine learning algorithms to forecast the rates of hotel rooms based on various factors such as date, location, room type, demand, and historical prices.

Hospitality 52

Hospitality Datasets Algorithm Machine Learning 52

AltexSoft

AUGUST 25, 2021

But today’s programs, armed with machine learning and deep learning algorithms, go beyond picking the right line in reply, and help with many text and speech processing problems. For example, tokenization (splitting text data into words) and part-of-speech tagging (labeling nouns, verbs, etc.) Assessing text data quality.

Process 139

Process Deep Learning Datasets Machine Learning 139

AltexSoft

AUGUST 22, 2022

You may already have a data catalog with the key business terms and their relations to one another. When connecting a new data source to your data catalog, the AI algorithms must be able to reuse the knowledge of the existing data sources to infer metadata about the new source. Data delivery.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Knowledge Hut

JUNE 28, 2023

Data Mining vs Business Intelligence: Methods and Techniques Data Mining: Data Mining Process in Business Intelligence utilizes a range of methods and techniques, including machine learning algorithms, statistical analysis, clustering, classification, association rule mining, natural language processing, and more.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52