Edureka

MARCH 26, 2025

Non-linear Transformation: By utilizing activation functions such as ReLU, sigmoid, or tanh, hidden layers augment the network’s ability to learn from data that isn’t limited to linearly separable information. Data Preprocessing: Tools for cleaning, normalizing, and augmenting data to ensure accuracy and relevance.

Raw Data 40

Raw Data Architecture Deep Learning Finance 40

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. 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.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Sync Computing

NOVEMBER 7, 2024

Depending on what sort of leaky analogy you prefer, data can be the new oil , gold , or even electricity. Of course, even the biggest data sets are worthless, and might even be a liability, if they arent organized properly. Data collected from every corner of modern society has transformed the way people live and do business.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

JULY 27, 2021

Google singles out four key phases through which a recommender system processes data. They are information collection, storing, analysis, and filtering. Data collection. The initial phase involves gathering relevant data to create a user profile or model for prediction tasks. Let’s have a closer look at each phase.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Knowledge Hut

JANUARY 19, 2024

Data Structures Data structures are the architects of data manipulation. Deep Learning Deep Learning takes machine learning to the next level, exploring neural networks and advanced techniques. Importance: Analyzes and interprets data collected over time.

Data Science 52

Data Science Machine Learning Algorithm Datasets 52

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. Another reason to use PySpark is that it has the benefit of being able to scale to far more giant data sets compared to the Python Pandas library.

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

NOVEMBER 28, 2023

The data goes through various stages, such as cleansing, processing, warehousing, and some other processes, before the data scientists start analyzing the data they have garnered. The data analysis stage is important as the data scientists extract value and knowledge from the processed, structured data.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

U-Next

AUGUST 11, 2022

It is possible to transform massive amounts of unstructured and structured data into useful information by digitising them. The ability to identify the data-analytics solutions which can be most beneficial to the business’s success. The efficacy and accuracy of data can be increased through data cleansing and validation.

Data Science 40

Data Science Data Cleanse Unstructured Data Machine Learning 40

ProjectPro

OCTOBER 20, 2021

Data Science has taken off in the technology space, the job title data scientist even being crowned as the Sexiest Job of the 21 st Century. Let's understand where Data Science belongs in the space of Artificial Intelligence. 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

ProjectPro

AUGUST 24, 2021

Google BigQuery receives the structured data from workers. Finally, the data is passed to Google Data studio for visualization. Learn how to use various big data tools like Kafka, Zookeeper, Spark, HBase, and Hadoop for real-time data aggregation. Strong proficiency in using SQL for data sourcing.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 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. Concepts of deep learning can be used to analyze this dataset properly.

Big Data 52

Big Data Coding Project Hadoop 52

Edureka

APRIL 1, 2025

Data augmentation is critical for boosting the performance of machine learning models, particularly deep learning models. The quality, amount, and importance of training data are important for how well these models perform. One of the main problems with using machine learning in real life is not having enough data.

Datasets 40

Datasets Machine Learning Deep Learning Data 40