AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

MAY 31, 2023

AI finds its use in a wide range of applications like marketing , automation, transport, supply chain, and communication, to name a few. The development process may include tasks such as building and training machine learning models, data collection and cleaning, and testing and optimizing the final product.

Project 96

Project Transportation Healthcare Deep Learning 96

Confluent

JUNE 13, 2019

You might think that data collection in astronomy consists of a lone astronomer pointing a telescope at a single object in a static sky. While that may be true in some cases (I collected the data for my Ph.D. thesis this way), the field of astronomy is rapidly changing into a data-intensive science with real-time needs.

Kafka 102

Kafka Bytes Data Pipeline Python 102

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 Healthcare 59

ProjectPro

JUNE 6, 2025

Neural networks refer to the series of algorithms implemented to determine the relationships between the datasets using a process that is in line with the operations of a human brain. You will be required to process the data before the training data and patterns are presented to the network. What is a Simple Neural Network?

Project 40

Project Deep Learning Banking Algorithm 40

Striim

JULY 10, 2024

From forecasting demand to managing operational risks, predictive analytics provides invaluable insights that empower organizations to make data-driven decisions in real-time. Predictive analytics in logistics involves utilizing statistical algorithms and machine learning techniques to analyze historical data.

Management 52

Management Transportation High Quality Data Machine Learning 52

ProjectPro

JUNE 6, 2025

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Knowledge Hut

JUNE 26, 2023

Use Stack Overflow Data for Analytic Purposes Project Overview: What if you had access to all or most of the public repos on GitHub? As part of similar research, Felipe Hoffa analysed gigabytes of data spread over many publications from Google's BigQuery data collection. Which queries do you have?

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

ProjectPro

APRIL 17, 2015

Last year when Twitter and IBM announced their partnership it seemed an unlikely pairing, but the recent big data news on New York Times about this partnership took a leap forward with IBM’s Watson all set to mine Tweets for sentiments.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 52

Confluent

FEBRUARY 6, 2019

After all, machine learning with Python requires the use of algorithms that allow computer programs to constantly learn, but building that infrastructure is several levels higher in complexity. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework.

Machine Learning 107

Machine Learning Python Kafka Java 107

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 Transportation ETL Tools 52

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

JANUARY 24, 2024

Tool Proficiency: Utilizing a diverse set of tools and technologies, including R, Tableau, Python, Matlab, Hive, Impala, PySpark, Excel, Hadoop, SQL, and SAS, to manipulate and analyze data efficiently. Complexity Simplification : Streamlining intricate data problems to make them more approachable and solvable.

Database-centric 52

Database-centric Data Science Machine Learning Algorithm 52

ProjectPro

NOVEMBER 18, 2021

Data science has been a trending buzzword in recent times. With wide applications in various sectors like healthcare, education, retail, transportation, media, and banking -data science applications are at the core of pretty much every industry out there. Plot histograms, heatmaps to get a better understanding of the dataset.

Data Science 52

Data Science Project Food Pharmaceutical 52

Knowledge Hut

APRIL 25, 2024

Only one in three data scientists claim to be specialist in geographical analysis, indicating that there are still very few spatial data scientists. Generally, five key steps comprise the standard workflow for spatial data scientists, which takes them from data collection to offering business insights after the process.

Data Science 52

Data Science Telecommunication Transportation Big Data 52

Edureka

FEBRUARY 16, 2023

This data can come from various sources, including government reports, trade publications, company earnings reports and surveys of consumers’ buying habits. This helps businesses reduce storage, transportation and waste costs while ensuring there’s always enough stock available to meet customers’ needs without overstocking.

Transportation 52

Transportation Government Certification Big Data 52

AltexSoft

DECEMBER 21, 2021

Synthetic data development. Synthetic data is an artificially generated dataset with labels that comes as an alternative to real-world data. It is created by computer simulations or algorithms and is often used to train machine learning models. It is possible to render as much synthetic data as needed for the project.

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

Knowledge Hut

DECEMBER 27, 2023

They are responsible for coordinating with production, warehouse, distribution and transportation. 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). In short, to get more profits.

Banking 52

Banking Recruitment Finance Portfolio 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

It can also be connected with Azure Bot Services to extract information from data collected via the bot interface. It uses time-series data and automatically selects the most relevant anomaly detection algorithm for detecting dips, deviations, and spikes from inliers.

Project 52

Project Transportation Data Pipeline Data Ingestion 52

ProjectPro

JUNE 6, 2025

These domains include: Data Preprocessing or Data Preparation lays the foundation by cleaning, transforming, and organizing raw data, ensuring it's ready for analysis and model training. It is crucial for algorithms sensitive to varying magnitudes of input data.

Python 40

Python Deep Learning Machine Learning Algorithm 40

ProjectPro

JUNE 6, 2025

FAQs on Big Data Projects What is a Big Data Project? A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on structured and unstructured data for several purposes, including predictive modeling and other advanced analytics applications.

Big Data 40

Big Data Coding Project Hadoop 40

ProjectPro

JUNE 6, 2025

It includes a carefully curated collection of more than 653 public datasets that have been well-documented and categorized for various research and educational uses. As a foundational resource for ML research, the UCI Machine Learning Repository offers sample data sets for algorithm development and evaluation.

Datasets 40

Datasets Data Science Project Google Cloud 40

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. Thus, crime levels in these locations decreased as a result of Data Analytics software. Predictive Analytics.

Data Analytics 40

Data Analytics Insurance Transportation Healthcare 40

Edureka

MARCH 26, 2025

Algorithmic Trading: Predicting stock trends using historical data for automated trading strategies. Transportation and Logistics: Autonomous Vehicles: Neural networks enable self-driving cars to recognize objects, predict motion, and make decisions. Quality Control: Automated defect detection in production lines using CNNs.

Raw Data 40

Raw Data Architecture Finance Deep Learning 40

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Advanced data scientists can use supervised algorithms to predict future trends.

Big Data 52

Big Data Coding Project Hadoop 52

U-Next

MARCH 15, 2023

Data Analytics for Gaining Insights The operational, strategic, and tactical decision-making processes heavily depend on information. However, the calculation and data collection within businesses is increasing swiftly. Smart Agents Online group purchasing is popular with consumers.

Management 52

Management Manufacturing Electronics Machine Learning 52

Knowledge Hut

JANUARY 11, 2024

Novo Nordisk uses the Linguamatics NLP platform from internal and external data sources for text mining purposes that include scientific abstracts, patents, grants, news, tech transfer offices from universities worldwide, and more. UPS utilizes supply chain data analysis in all aspects of its shipping process.

Data Science 98

Data Science Transportation Hospitality Banking 98

ProjectPro

JUNE 6, 2025

An approach to performing customer market basket analysis can be done using Apriori and Fp Growth data mining algorithms. Source Code: Market Basket Analysis using Apriori and Fp Growth Algorithms 2) Reducing Manufacturing Failures Product-based companies have the task of ensuring that their products are top of the notch.

Data Analytics 40

Data Analytics Project Insurance Datasets 40

Edureka

MARCH 27, 2025

Companies can make hiring processes that are fair and support equality by checking algorithms and making sure they use a variety of training data. Companies are reducing their impact on the environment by improving algorithms, using green energy sources, and reducing the amount of work that computers have to do.

Healthcare 40

Healthcare Education Technology Systems 40