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 Engineering 98

Data Engineering Data Engineer Coding Project 98

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

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 Big Data Certification 52

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

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

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

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 Finance Recruitment Portfolio 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

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 Engineering 40

Data Engineering Data Engineer Engineering Hadoop 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

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

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

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 Machine Learning Electronics 52