ProjectPro

JULY 9, 2021

Suppose you’re among those fascinated by the endless possibilities of deep learning technology and curious about the popular deep learning algorithms behind the scenes of popular deep learning applications. Table of Contents Why Deep Learning Algorithms over Traditional Machine Learning Algorithms? What is Deep Learning?

Deep Learning 40

Deep Learning Algorithm Machine Learning Datasets 40

Knowledge Hut

MAY 3, 2024

Analytics - Spark can be very useful when building real-time analytics from a stream of incoming data. E-commerce - Information about the real-time transaction can be passed to streaming clustering algorithms like alternating least squares or K-means clustering algorithm.

Scala 98

Scala Hadoop Healthcare Big Data 98

Cloudera

NOVEMBER 14, 2023

Credit scoring and risk assessment: Traditional credit scoring models rely on narrow and limited financial data, making it difficult for individuals without a well-established credit history to access loans or other financial products.

Banking 74

Banking Education Unstructured Data Algorithm 74

Data Engineering Podcast

FEBRUARY 24, 2019

To help other people find the show please leave a review on iTunes , or Google Play Music , tell your friends and co-workers, and share it on social media. What is your litmus test for whether to use deep learning vs explicit ML algorithms or a basic decision tree? What are your thoughts on that layer of the build vs buy decision?

Deep Learning 100

Deep Learning Data Engineer Data Engineering Engineering 100

Knowledge Hut

APRIL 23, 2024

Big Data Use Cases in Customization and the Customer Experience Enhancing Customer Journeys and Experiences: Big data analytics examines data from several touchpoints, including websites, mobile applications, customer care, and social media, to assist firms in understanding the whole customer experience.

Big Data 52

Big Data Recruitment Retail Transportation 52

Cloudera

OCTOBER 28, 2020

To start, they look to traditional financial services data, combining and correlating account activity, borrowing history, core banking, investments, and call center data. Rabobank runs sophisticated machine learning algorithms and financial models to help customers manage their financial obligations, including loan repayments. .

Unstructured Data 73

Unstructured Data Banking Machine Learning Media 73

Knowledge Hut

MAY 2, 2024

Streaming Data: Streaming is basically unstructured data produced by different types of data sources. MLlib has multiple algorithms for Supervised and Unsupervised ML which can scale out on a cluster for classification, regression, clustering, collaborative filtering.

Scala 52

Scala Hospitality Healthcare Machine Learning 52

ProjectPro

FEBRUARY 16, 2023

The study and pattern of how humans think is the foundation of artificial intelligence, and the algorithm replicates human brain functions. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems. Tools OLAP, data visualization, reporting, and dashboards.

Business Intelligence 52

Business Intelligence BI Data Mining Algorithm 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. This information is gathered from a variety of sources, including sensor readings, social media engagements, and client transactions. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

DECEMBER 26, 2023

Importance of Big Data Companies Big Data is intricate and can be challenging to access and manage because data often arrives quickly in ever-increasing amounts. Both structured and unstructured data may be present in this data. Microsoft's Big Data strategy is broad and expanding rapidly.

Big Data 52

Big Data Unstructured Data Amazon Web Services Hadoop 52

U-Next

AUGUST 18, 2022

Data Science may combine arithmetic, business savvy, technologies, algorithm, and pattern recognition approaches. These factors all work together to help us uncover underlying patterns or observations in raw data that can be extremely useful when making important business choices. Theaters, channels, etc.,

Unstructured Data 40

Unstructured Data Data Science Medical Business Intelligence 40

Cloudera

OCTOBER 21, 2020

The Insurance industry is in uncharted waters and COVID-19 has taken us where no algorithm has gone before. Instead of in-person appointments or walkthroughs, insurance companies may now rely on drone footage, satellite imagery, social media posts, and mobile apps that gather data on customers. CLOUD-ENABLED EVOLUTION .

Insurance 72

Insurance Unstructured Data Hospitality Media 72

Knowledge Hut

MAY 31, 2023

Artificial intelligence has had a profound impact on our daily lives, and we employ AI whenever you look through social media, open Spotify, or conduct a fast Google search. Currently, most students and working professionals prefer a Data Science Course to make a smooth transition in the data science field.

Project 96

Project Healthcare Deep Learning Transportation 96

Knowledge Hut

OCTOBER 26, 2023

This AWS project example is highly relevant nowadays when social media is widely using content recommendation systems to present things of our interest. It comes with in-built ML algorithms that do not require label data and leverages semantic search to simplify tasks. Source code: GitHub 5.

AWS 52

AWS Coding Project Cloud Computing 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

U-Next

SEPTEMBER 9, 2022

The platform distributes Hadoop large data and analytics operations among computer cluster nodes, breaking them down into smaller workloads that may be handled in parallel. Hadoop can scale up from a single server to thousands of servers and analyze organized and unstructured data. . What is Hadoop in Big Data? .

Hadoop 40

Hadoop Big Data Management Unstructured Data 40

Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

Knowledge Hut

JUNE 26, 2023

For this study, we wanted to create a "big data pipeline for user sentiment analysis on the US stock market." In a nutshell, this initiative uses social media data to provide real-time market sentiment predictions. Source Code: Smart Cities Using Big Data 3. Source Code: Tourist Behavior Analysis 4.

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. Recommendation engines are popular in media, entertainment, and shopping. This type of application is beneficial in searching, mobile application development, and social media apps.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Edureka

JULY 18, 2023

To find abnormalities and signs of cyber risks, machine learning algorithms analyse vast volumes of data, including log files, user behaviour patterns, and network traffic. Transaction Monitoring: AI systems examine enormous volumes of transactional data to spot patterns and anomalies that could be signs of fraud.

Banking 40

Banking Algorithm Media Machine Learning 40

Knowledge Hut

JULY 26, 2023

Facebook, on the other hand, as a social media giant, has created its own database solutions to handle large amounts of user data. It is widely utilized for its great scalability, fault tolerance, and quick write performance, making it ideal for large-scale data storage and real-time analytics applications.

Database 52

Database NoSQL Telecommunication MongoDB 52

Monte Carlo

MAY 28, 2024

Popular Data Ingestion Tools Choosing the right ingestion technology is key to a successful architecture. Common Tools Data Sources Identification with Apache NiFi : Automates data flow, handling structured and unstructured data. Used for identifying and cataloging data sources.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Striim

SEPTEMBER 11, 2024

A well-designed data pipeline ensures that data is not only transferred from source to destination but also properly cleaned, enriched, and transformed to meet the specific needs of AI algorithms. Why are data pipelines important? Where does Striim Come into Play When Building Data Pipelines?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Knowledge Hut

JUNE 23, 2023

The key advantage of adaptive analytics is that businesses can make choices based on real-time data with incredibly high accuracy What is Real-time Analytics? Real-time data analytics is quickly analyzing data to provide actionable insights for enterprises. Who Uses Real-time Data Analytics?

Data Analytics 52

Data Analytics IT Transportation Analytics Architecture 52

Knowledge Hut

DECEMBER 27, 2023

Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? Big data is often denoted as three V’s: Volume, Variety and Velocity. Big data is often denoted as three V’s: Volume, Variety and Velocity.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

JUNE 20, 2023

Examples Pull daily tweets from the data warehouse hive spreading in multiple clusters. Facial reorganization, social media optimization, etc. They transform unstructured data into scalable models for data science. Analyze trends and patterns Conduct in-depth data analysis, then present the findings.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

Knowledge Hut

JULY 26, 2023

This velocity aspect is particularly relevant in applications such as social media analytics, financial trading, and sensor data processing. Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Handling this variety of data requires flexible data storage and processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Knowledge Hut

APRIL 25, 2024

Variety: Unstructured data, semi-structured data, and raw data are only a few examples of the variety of data kinds that exist. It is effective to use a recommendation engine that makes use of data filtering technologies that gather data and then filter it using algorithms.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

U-Next

SEPTEMBER 22, 2022

Several vetted models and algorithms are used in the predictive analytics tools in order to generate a large number of useful outcomes that are applicable to a wide range of use cases. . Understanding The Types Of Predictive Modeling Algorithms . Listed below are some of the different types of predictive modeling algorithms: .

Hospitality 40

Hospitality Algorithm Machine Learning Banking 40

AltexSoft

JULY 27, 2021

By utilizing ML algorithms and data, it is possible to create smart models that can precisely predict customer intent and as such provide quality one-to-one recommendations. At the same time, the continuous growth of available data has led to information overload — when there are too many choices, complicating decision-making.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Knowledge Hut

JULY 24, 2023

Continuous queries are designed to process and analyze data as it arrives. Therefore, they are often used in applications that require real-time monitoring or processing, such as financial trading, IoT devices, or social media sentiment analysis. Ad-hoc queries help perform exploratory analysis or troubleshooting.

Database 52

Database SQL Process NoSQL 52

AltexSoft

AUGUST 29, 2023

Unlike traditional DWs, cloud data warehouses like Snowflake, BigQuery, and Redshift come pre-equipped with advanced features; learn more about the differences in our dedicated article. Unlike data warehouses, data lakes allow a schema-on-read approach, enabling greater flexibility in data storage.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

U-Next

AUGUST 11, 2022

It’s a study of Computer Algorithms, which helps self-improvement through experiences. It builds a model based on Sample data and is designed to make predictions and decisions without being programmed for it. It’s a subset of ML which is capable of learning from unstructured data. ML And AI Are The Future.

Medical 52

Medical Computer Science Scala Machine Learning 52

Cloudera

OCTOBER 30, 2018

The abundant growth of data, maturation of machine algorithms, and future regulatory compliance demands from the European Union’s General Data Protection Regulation (GDPR) will shift the landscape for creating a single source of the truth for customer data.

Unstructured Data 42

Unstructured Data Data Lake Algorithm Machine Learning 42

Knowledge Hut

MARCH 27, 2024

Big data tools are used to perform predictive modeling, statistical algorithms and even what-if analyses. Some important big data processing platforms are: Microsoft Azure. Why Is Big Data Analytics Important? Data can be processed for the application of big data analysis over the cloud and segregated using Xplenty.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

MARCH 17, 2021

Machine learning makes use of a set of learning algorithms (supervised or unsupervised learning process) to analyze the data, interpret it, learn from it, and make the best possible business decisions based on the learnings. But how will the ML algorithm know which one is Apple and which one is Orange?

Deep Learning 52

Deep Learning Machine Learning Algorithm Data Science 52