RandomTrees

SEPTEMBER 10, 2024

Consequently, many industries, including manufacturing, energy, transportation, and healthcare, are adopting predictive maintenance as their preferred strategy. AI algorithms analyze massive sensor-collected data from machines containing temperature, vibration, and pressure, among other operational parameters.

Transportation 59

Transportation Manufacturing Machine Learning Algorithm 59

Knowledge Hut

MAY 2, 2024

It means a computer or a system designed with machine learning will identify, analyse and change accordingly and give the expected output when it comes across a new pattern of data, without any need of humans. It means computers learn and there are many concepts, methods, algorithms and processes involved in making this happen.

Machine Learning 98

Machine Learning IT Deep Learning Algorithm 98

Knowledge Hut

DECEMBER 29, 2023

Learning Outcomes: You will understand the processes and technology necessary to operate large data warehouses. Engineering and problem-solving abilities based on Big Data solutions may also be taught. Learning Outcomes: Acquire the skills necessary to assess models developed from data.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

DECEMBER 27, 2023

Many industries, such as medicine, business, technology, defense, aerospace, marketing, and manufacturing, need a team of software developers to ensure their businesses' maximum performance and introduce innovative software and technologies. They make sure that all enterprise applications run smoothly at any cost.

Medical 98

Medical Programming Language Amazon Web Services Entertainment 98

Knowledge Hut

DECEMBER 21, 2023

IoT: Overview IoT has numerous applications in various sectors such as healthcare, agriculture, transportation, manufacturing, and smart cities. The data collected from IoT devices can be used to improve decision-making, optimize processes, and enhance customer experiences.

Coding 98

Coding Transportation Medical Retail 98

Grouparoo

DECEMBER 7, 2021

If undetected, corruption of data and its information will compromise the processes that utilize that data. Personal Data Collecting and managing data carries regulatory responsibilities regarding data protection and evidence required for regulatory compliance.

Data Integration 52

Data Integration Manufacturing ETL Tools Transportation 52

Knowledge Hut

JUNE 26, 2023

Multiple types of data exist within organizations, and it is the obligation of data architects to standardize them so that data analysts and scientists can use them interchangeably. If data scientists and analysts are pilots, data engineers are aircraft manufacturers. Which queries do you have?

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

APRIL 25, 2024

Recognizing the difference between big data and machine learning is crucial since big data involves managing and processing extensive datasets, while machine learning revolves around creating algorithms and models to extract valuable information and make data-driven predictions.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Knowledge Hut

DECEMBER 21, 2023

Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing Cloud computing research topics are getting wider traction in the Cloud Computing field. The NN-MOEA algorithm utilizes neural networks to optimize multiple objectives, such as planning, cost, and resource utilization.

Cloud Computing 52

Cloud Computing Cloud Algorithm Healthcare 52

Knowledge Hut

DECEMBER 26, 2023

This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc. This is one of the major reasons behind the popularity of data science.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection. from tons of free online resources.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

RandomTrees

JANUARY 29, 2024

Traditionally, the quest for labeled data involves the meticulous task of human annotation, a process both labor-intensive and financially demanding. Yet, beyond the sheer toil, there are lurking concerns of privacy, limitations in data diversity, and the uphill battle of scaling up real-world data collection.

Medical 52

Medical Retail Entertainment Datasets 52

Knowledge Hut

NOVEMBER 20, 2023

Automation is more prevalent in the manufacturing, administrative, logistics, and optimization industries. Robotic process automation (RPA), data entry, manufacturing, etc. This is done in the following sequence: Data collection, Data processing, Feature extraction, Model selection, Training.

Manufacturing 52

Manufacturing Pharmaceutical Healthcare Finance 52

Netflix Tech

JULY 21, 2022

Some features (as an example) include Device Type ID, SDK Version, Buffer Sizes, Cache Capacities, UI resolution, Chipset Manufacturer and Brand. Now we can use any multi-class classification algorithm?—?ANNs, Some nuances while creating this dataset come from the on-field domain knowledge of our engineers.

Machine Learning 75

Machine Learning Datasets Big Data Data Pipeline 75

Monte Carlo

FEBRUARY 21, 2023

Reduced reliance on IT Integral to a data fabric is a set of pre-built models and algorithms that expedite data processing. That means your data fabric should be constantly ingesting, analyzing, and leveraging metadata through graph models that present that metadata in an easily digestible, user-friendly way.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Reduced reliance on IT Integral to a data fabric is a set of pre-built models and algorithms that expedite data processing. That means your data fabric should be constantly ingesting, analyzing, and leveraging metadata through graph models that present that metadata in an easily digestible, user-friendly way.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

ProjectPro

NOVEMBER 18, 2021

Analysis of Big data also helps them understand new item sales, make decisions on discontinuing products, and the performance of brands. Walmart runs a backend algorithm that estimates this based on the distance between the customer and the fulfillment center, inventory levels, and shipping methods available.

Data Science 52

Data Science Project Food Pharmaceutical 52

Knowledge Hut

JUNE 20, 2023

For example, AI can analyze sensor data from manufacturing equipment and detect when equipment is operating outside of normal parameters. Data Collection and Management Techniques of a Qualitative Research Plan Any qualitative research calls for the collection and management of empirical data.

Database 52

Database Java Education Data Collection 52

Knowledge Hut

NOVEMBER 15, 2023

Example 4: To utilize my background in mechanical engineering to improve the efficiency of manufacturing processes for a leading automotive company. Example 7: To use my skills in industrial engineering to streamline operations and improve the bottom line for a manufacturing company. Example 7: A qualified Q.A.

Finance 98

Finance Certification Database-centric Business Intelligence 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.

Data Analytics 52

Data Analytics IT Transportation Analytics Architecture 52

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

Knowledge Hut

JULY 3, 2023

Real-time data ingestion often deals with various systems logs from various sectors like manufacturing, finance, cybersecurity, and e-commerce. Operational Analytics: Real-Time data ingestion strengthens attributes of monitoring and analyzing operational data in real-time.

Data Ingestion 52

Data Ingestion Google Cloud Pipeline-centric Media 52

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

FEBRUARY 1, 2024

Your workflow should start with data cleaning. You may likely duplicate or incorrectly classify data while working with large datasets and merging several data sources. Your algorithms and results will lose their accuracy if you have wrong or incomplete data.

Data Science 52

Data Science Process Data Cleanse Datasets 52

ProjectPro

MARCH 14, 2014

As the big data boom spreads globally, we at ProjectPro describe on how big data helps business across different industries and the companies using big data that stand to gain the most from implementing big data initiatives. Work on Interesting Big Data and Hadoop Projects to build an impressive project portfolio!

Hadoop 40

Hadoop Big Data Data Mining Retail 40

ProjectPro

JUNE 2, 2015

May 26, Wall Street Journal: “Big Data Brings Relief to Allergy Medicine Supply Chains” Bayer AG a manufacturer of the allergy drug Claritin is using big data to get ahead of the seasonal trends. times better than those with ad-hoc or decentralized teams.

Big Data 40

Big Data Hadoop Banking Data Analytics 40

Knowledge Hut

DECEMBER 27, 2023

Supply Chain Executive Supply Chain Executives are responsible for how companies drive the smooth flow of goods from manufacturing to delivery. A career in Data Science Data Science is a study interrelated and disciplinary field that employs maths, science algorithms, advanced analytics, and Artificial Intelligence(AI).

Banking 52

Banking Recruitment Finance Portfolio 52

Edureka

MARCH 26, 2025

Algorithmic Trading: Predicting stock trends using historical data for automated trading strategies. Predictive Analytics: Forecasting patient outcomes and optimizing treatment plans using patient data. Manufacturing: Predictive Maintenance: Neural networks monitor machine performance to predict and prevent breakdowns.

Raw Data 40

Raw Data Architecture Deep Learning Finance 40

U-Next

AUGUST 24, 2022

Robotics : Robots before behaviour are effective in organized situations where the work is repeated, like the production line of an automotive manufacturing facility. Traditional Machine Learning algorithms lack a sense of the big picture and are created to excel at particular subtasks. Work in Unpredictable, Dynamic Circumstances.

Machine Learning 40

Machine Learning Algorithm Manufacturing Data Collection 40

ProjectPro

OCTOBER 20, 2021

The estimator automatically performs the algorithm selection as well as the hyperparameter tuning Auto-Keras : To recall, Keras is an open-source library that provides a Python interface into the world of Artificial Intelligence, especially Tensorflow. Auto-Weka : Weka is a top-rated java-based machine learning software for data exploration.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

U-Next

AUGUST 26, 2022

Data Analytics Illustration. Organizations may alter their company and environment electronically via the use of Data Analytics, rendering them more creative and forward in their judgment call. Here, we begin with the essential kind and work our way towards the more complex ones. Descriptive Analytics. Predictive Analytics.

Data Analytics 40

Data Analytics Insurance Transportation Healthcare 40

AltexSoft

APRIL 27, 2023

Efficient analysis of data from multiple sources helps pharma businesses identify market trends and develop targeted marketing strategies. Machine learning algorithms can be used to predict future sales of particular drugs or spot growth. The event harmonizer automates data collection and processing. Marketing and sales.

Data Analytics 52

Data Analytics Pharmaceutical Medical Manufacturing 52

U-Next

SEPTEMBER 21, 2022

Data mining is the systematic assessment of datasets to discover potentially relevant trends and correlations. The fundamental purpose of Data Mining is to process and obtain information from data collection. . Data mining is a broad and complex process with several components. . Disadvantages to Data Mining .

Data Mining 40

Data Mining Data Warehouse Business Intelligence Retail 40

U-Next

AUGUST 24, 2022

Examples of Data Abstraction in Weather Predictions. Predictions for the weather frequently rely on data-driven ideas and notions like “chance of rainfall.” ” Additionally, it uses algorithms to determine the collected data. Data abstraction also reduces error margins and intervals.

Data 40

Data Utilities Manufacturing Programming 40

U-Next

MARCH 15, 2023

Introduction Every industry is undergoing a technological revolution, and manufacturing is no exception. Additionally, made-to-order is the new standard in manufacturing, which itself is changing. Less inventory is needed, and a more real-time operating environment are requirements of just-in-time, lean manufacturing.

Management 52

Management Manufacturing Machine Learning Electronics 52

phData: Data Engineering

SEPTEMBER 27, 2024

Let’s break down why this is so powerful for us marketers: Data Preservation : By keeping a copy of your raw customer data, you preserve the original context and granularity. That’s essentially what a composable CDP lets you do with your customer data platform. Those days are gone!

Data 52

Data Raw Data Data Lake Architecture 52

Knowledge Hut

JANUARY 11, 2024

Data science has become popular in the last few years due to its successful application in making business decisions. Data scientists have been using data science techniques to solve challenging real-world issues in healthcare, agriculture, manufacturing, automotive, and many more.

Data Science 98

Data Science Transportation Banking Hospitality 98