Knowledge Hut

OCTOBER 30, 2023

Big data and Artificial Intelligence have been thriving in recent years, and the emphasis on these technologies will propel them to new heights. You can check out the best Big Data courses to have an in-depth idea about big data tools and technologies to prepare for a job in the domain. Source Code: Medical Insurance Fraud Detection 4.

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Big Data Coding Project Medical 52

Precisely

NOVEMBER 20, 2023

AI transforms how we interact with technology, make decisions, and solve complex problems. It makes table joins extremely fast and eliminates the need to deploy complex matching algorithms to associate addresses with their underlying attributes. From a data science perspective, this offers tremendous advantages.

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Knowledge Hut

APRIL 23, 2024

Go for the best Big Data courses and work on ral-life projects with actual datasets. Risk Management: By using big data to analyze a variety of datasets, risks associated with credit scoring, investment portfolios, and market volatility may be assessed and managed, assisting in the development of efficient risk reduction techniques.

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Knowledge Hut

JANUARY 22, 2024

Financial technology, popularly referred to as FinTech, is one of the fastest-growing areas of technological innovation and is popular with venture capitalists. FinTech refers to a set of technologies that focus on new ways of providing banking and financial services to consumers. Why is Data Science So Important?

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Data Science Banking Big Data Insurance 52

AltexSoft

NOVEMBER 17, 2021

So businesses employ machine learning (ML) and Artificial Intelligence (AI) technologies for classification tasks. Visual classification focuses on a visual structure of documents, employing computer vision and image recognition technologies. An example of document structure in healthcare insurance. Source: affine.ai.

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Knowledge Hut

JANUARY 16, 2024

With so much happening around machine learning, it is no surprise that any enthusiast who is keen on shaping their career in software programming and technology would prefer machine learning as a foundation to their career. It is the realm where algorithms self-educate themselves to predict outcomes by uncovering data patterns.

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ProjectPro

AUGUST 28, 2021

Projects help you create a strong foundation of various machine learning algorithms and strengthen your resume. Each project explores new machine learning algorithms, datasets, and business problems. In this ML project, you will learn to implement the random forest regressor and Xgboost algorithms to train the model.

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Precisely

JANUARY 31, 2023

Those bets are paying off, as business leaders discover the power of continuous analytics performed on very large datasets. Insurance carriers, for example, use AI to refine their understanding of risk, as well as to score incoming claims based on the likelihood that they are fraudulent.

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Knowledge Hut

NOVEMBER 27, 2023

Data Science is a field that uses scientific methods, algorithms, and processes to extract useful insights and knowledge from noisy data. Learn Data Analysis with Python Now that you know how to code in Python start picking toy datasets to perform analysis using Python. This is where Data Science comes into the picture.

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Data Science Healthcare Machine Learning Telecommunication 97

Monte Carlo

MARCH 28, 2023

Are data quality analysts still relevant with the emergence of new data pipeline monitoring technologies? Data quality analyst skills and tools Like data analysts, data quality analysts must be adept at separating meaningful trends and information from larger datasets. That is to say it’s changed a lot. How is their role evolving?

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Insurance Programming Language Manufacturing Healthcare 59

ProjectPro

DECEMBER 10, 2021

And one can easily comprehend the statistics if one considers the various industries (law enforcement, healthcare, education, finance, and technology) that can benefit from Business Intelligence tools. Additionally, use different machine learning algorithms like linear regression, decision trees, random forests, etc.

Business Intelligence 52

Business Intelligence Coding Project BI 52

Knowledge Hut

AUGUST 1, 2023

Machine learning is a way in which artificial intelligence is used to train algorithms or computers. Machine learning algorithms can analyze potentially tera bytes of data, identify patterns from these data, and make predictions or decisions. Early detection of anomalies allows for prompt intervention and proactive patient management.

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Knowledge Hut

JANUARY 11, 2024

For this purpose, a data enthusiast needs to stay updated with the latest technological advancements in AI. In this discussion, I will present some case studies to you that contain detailed and systematic data analysis of people, objects, or entities focusing on multiple factors present in the dataset.

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U-Next

OCTOBER 20, 2022

An inaccuracy known as bias in data occurs when specific dataset components are overweighted or overrepresented. In reality, computers, data, and algorithms are not entirely objective. It’s we, humans, that technologies and algorithms. Introduction . The key to overcoming bias is being aware of its warning signs.

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Knowledge Hut

DECEMBER 26, 2023

Data science develops predictive models using sophisticated machine learning algorithms. You can acquire and use data sets for free from various dataset sources. You can acquire and use data sets for free from various dataset sources. Additionally, they could get advantages like paid vacation days and health insurance.

Data Science 52

Data Science Portfolio Recruitment Education 52

Edureka

APRIL 17, 2023

Here are a few project ideas that are suitable for beginners: Analyzing a dataset to identify trends and patterns: One of the most common projects for beginners is to analyze a dataset to identify trends and patterns. As a beginner, you can start by learning how to use visualization tools like Tableau or Power BI.

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Knowledge Hut

DECEMBER 26, 2023

Data Science is the study of extracting insights from massive amounts of data using various scientific approaches, processes and algorithms. Data science, which solves problems by connecting relevant data for later use, aids these emerging technologies. What i s Data Science and Why is it Important?

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ProjectPro

JUNE 24, 2021

Machine learning and Natural language processing skills : Processing of the data may require algorithms and techniques from the fields of machine learning and natural language processing to be applied. Data analytics projects for practice help one identify their strengths and weaknesses with various big data tools and technologies.

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Data Analytics Project Insurance Hadoop 40

ProjectPro

OCTOBER 26, 2021

A machine learning framework is a tool that lets software developers, data scientists, and machine learning engineers build machine learning models without having to dig into the underlying working principle(math and stat) of the machine learning algorithms. Google Brain team is the brainchild behind this open-source framework.

Machine Learning 52

Machine Learning Programming Language Healthcare Deep Learning 52

ProjectPro

OCTOBER 8, 2021

To build a customer segmentation machine learning model, you can use unsupervised machine learning algorithms like K- Means Clustering. You can start by downloading the Online Retail Dataset. Perform exploratory data analysis of the dataset to understand the various attributes in the dataset better.

Retail 52

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ProjectPro

OCTOBER 27, 2021

There is a wide range of open-source machine learning algorithms and tools that fit exceptionally with financial data. You can start the stock price prediction project by applying simple ML algorithms like Averaging and Linear Regression. Also, remove all missing and NaN values from the dataset, as incomplete data is unnecessary.

Finance 52

Finance Machine Learning Project Banking 52

Cloudera

APRIL 6, 2022

AI requires good data and strong training algorithms, such as through machine learning, to make decisions about what data to send back to decision-makers. To note, previous satellites had trouble with clouds and this satellite launched with technology to fix the issue. .

Big Data 101

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ProjectPro

OCTOBER 22, 2021

Seamless and rapid integration of AI and cloud-based technology has given rise to a massive demand for artificial intelligence and cloud computing professionals. It uses time-series data and automatically selects the most relevant anomaly detection algorithm for detecting dips, deviations, and spikes from inliers.

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AltexSoft

OCTOBER 22, 2021

Well, the technology behind such “magic” is called deep learning. Deep learning is a subfield of machine learning where artificial neural networks — complex algorithms modeled to work in a way similar to human brains — learn from large sets of data. Because there are shoes so advanced that they gained the name of “technology doping.”

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U-Next

AUGUST 26, 2022

Algorithm-driven firms are the new inventors and corporate executives because they go well beyond typical KPI measurement and reviewing to uncover hidden patterns. Prescriptive Analytics is complex to deploy and maintain since it makes use of cutting-edge tools and technology, including machine learning, business requirements, and algorithms.

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Towards Data Science

OCTOBER 7, 2023

We dug deep into the early adopters’ strategies to learn how companies are putting this technology to use today — and what it takes for a data team to implement gen-AI at scale. What generative AI use cases are realistic, achievable, and actually worth the ROI? Tools like Tensorflow and HuggingFace are good options to fine-tune your models.

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Unstructured Data Finance SQL Media 74

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Set up data storage technology. What is data collection? Find sources of relevant data.

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Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

OCTOBER 4, 2023

We dug deep into the early adopters’ strategies to learn how companies are putting this technology to use today — and what it takes for a data team to implement gen AI at scale. What generative AI use cases are realistic, achievable, and actually worth the ROI? Tools like Tensorflow and HuggingFace are good options to fine-tune your models.

Unstructured Data 72

Unstructured Data Finance SQL Media 72

U-Next

AUGUST 3, 2022

Now that well-known technologies like Hadoop and others have resolved the storage issue, the emphasis is on information processing. A Data Scientist is skilled in concluding data using various systems, procedures, and algorithms. Up until 2010, it was extremely difficult for companies to store data.

Retail 52

Retail Data Science Computer Science Entertainment 52

AltexSoft

SEPTEMBER 19, 2023

External travel data sources and providers External data encompasses all types of information and datasets created outside a company and existing beyond its direct control, ownership, or management. For instance, a notable expert in this domain, OAG , has a suite of air-related datasets, including historical flight data spanning 20 years.

Hospitality 52

Hospitality Machine Learning Data Governance BI 52

ProjectPro

DECEMBER 14, 2021

AutoML Cashflow Optimization for Insurance Company 8. Regardless of the data source, query editors are helpful for editing datasets. In the query editor, you can perform changes like renaming a dataset and removing one or more columns, among other things. You can use Microsoft's sample dataset.

BI 52

BI Project Business Intelligence Datasets 52

Knowledge Hut

JULY 26, 2023

Columnar stores, such as Apache Cassandra and Apache HBase, organize data by columns rather than rows, allowing for faster read and write operations on huge datasets. They provide specialized data types and indexing algorithms for storing and querying map, coordinate, and spatial relationship information. Spatial Database (e.g.-

Database 52

Database NoSQL Telecommunication MongoDB 52

Knowledge Hut

DECEMBER 26, 2023

Business intelligence (BI) is the collective name for a set of processes, systems, and technologies that turn raw data into knowledge that can be used to operate enterprises profitably. Business intelligence solutions comBIne technology and strategy for gathering, analyzing, and interpreting data from internal and external sources.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

ProjectPro

APRIL 1, 2021

A 2020 Dice report said that the demand for data scientists increased by an average of 50% across healthcare, telecommunications, media, and the banking, financial services, and insurance (BFSI) sectors, among others. When I was a student I thought about starting something to talk about emerging technologies.

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U-Next

SEPTEMBER 21, 2022

Data mining is the systematic assessment of datasets to discover potentially relevant trends and correlations. When it comes to tools, various ones operate with different sorts of data mining, depending on the algorithms they use. Investment and Insurance sector . What is Data Mining? . Disadvantages to Data Mining .

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ProjectPro

AUGUST 24, 2021

But before you send out your resume for any data engineer job, and if you want to get shortlisted for further rounds, you need to have ample knowledge of various data engineering technologies and methods. 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

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. NLP offers several solutions to help doctors from speech-to-text transcribing technology to simplified clinical documentation management.

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