AltexSoft

OCTOBER 22, 2021

Well, the technology behind such “magic” is called deep learning. In this post, we’ll explain what deep learning is, how it works, how it’s different from traditional machine learning, and what areas it can be applied within. Get ready because you’re about to go deep into deep learning.

Deep Learning 52

Deep Learning Raw Data Algorithm Machine Learning 52

Knowledge Hut

JANUARY 22, 2024

Over time, FinTech has evolved to disrupt almost all aspects of financial services, including payments, investments, consumer finance, insurance, securities settlement, cryptocurrencies, etc. FinTech companies depend heavily on FinTech data science to simplify financial decision-making and deliver cutting-edge solutions.

Data Science 52

Data Science Banking Big Data Insurance 52

Knowledge Hut

NOVEMBER 27, 2023

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 is a field that uses scientific methods, algorithms, and processes to extract useful insights and knowledge from noisy data.

Data Science 97

Data Science Healthcare Machine Learning Telecommunication 97

AltexSoft

NOVEMBER 17, 2021

An example of document structure in healthcare insurance. Another example is the insurance industry that processes tens of thousands of claims daily. It requires extracting raw data from claims automatically and applying NLP for analysis. It makes data much easier for the algorithm to digest during the training process.

Machine Learning 75

Machine Learning Insurance Medical Healthcare 75

U-Next

AUGUST 3, 2022

After understanding what Data Science is and its fundamental principles, what else do we need to discuss? What is a Data Scientist? A Data Scientist is skilled in concluding data using various systems, procedures, and algorithms. The people who have inquiries about data are known as Data Scientists.

Retail 52

Retail Data Science Computer Science Entertainment 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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