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

FEBRUARY 1, 2024

What is Data Cleaning in Data Science? Data cleaning is the process of identifying and fixing incorrect data. Various fixes can be made to the data values representing incorrectness in the data. Some data pipeline systems also allow you to resume the pipeline from the middle, thus, saving time.

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U-Next

OCTOBER 16, 2022

From business transactions to scientific data, sensor data, pictures, videos, and more, we can and are handling a tremendous amount of information and data every day. The KDD process in data mining is used in business in the following ways to make better managerial decisions: . What is KDD? .

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Knowledge Hut

JANUARY 18, 2024

and In my view, Data Science primarily focuses on engineering, processing, interpreting, and analyzing data to facilitate effective and informed decision-making. Strong A I is made of two components which are Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI).

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Knowledge Hut

JULY 7, 2023

Machine learning is a part of AI (artificial intelligence) that focuses on developing various algorithms and models to make decisions without human intervention. Various algorithms and models are trained using machine learning techniques like supervised, unsupervised, reinforcement, etc. How Does Machine Learning Work?

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Knowledge Hut

JULY 4, 2023

This can be done by finding regularities in the data, such as correlations or trends, or by identifying specific features in the data. Pattern recognition is used in a wide variety of applications, including Image processing, Speech recognition, Biometrics, Medical diagnosis, and Fraud detection.

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Knowledge Hut

MAY 2, 2024

Doesn’t this piece of information gives you a glimpse of the wondrous possibilities of machine learning and its potential uses? 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.

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Knowledge Hut

DECEMBER 26, 2023

You can execute this by learning data science with python and working on real projects. These skills are essential to collect, clean, analyze, process and manage large amounts of data to find trends and patterns in the dataset. Along with business understanding, you also need to have analytical skills.

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Knowledge Hut

JANUARY 18, 2024

What is Data Science? Data science is a collaborative field that deals with the study of data using various tools and methods. It aims to find invisible patterns, extract meaningful information, and solve problems in various domains. Know more about data science vs business analytics.

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Data Science Computer Science Programming Language Machine Learning 96

Cloudera

APRIL 13, 2022

If you’re AI-first, that means you have figured out how to leverage artificial intelligence to boost organizational agility so you can continuously adapt operational processes to deliver the right business outcomes. . Data collection and interpretation when purchasing products and services can make a big difference. Procurement.

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Knowledge Hut

MAY 9, 2024

Data science is an interdisciplinary academic domain that utilizes scientific methods, scientific computing, statistics, algorithms, processes, and systems to extrapolate or extract knowledge and insights from unstructured, structured, and noisy data. They manage data storage and the ETL process.

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

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

AltexSoft

DECEMBER 21, 2021

Others believe that such machines simply consume information and learn from it by themselves. Computer systems have limited capabilities without human guidance, and data labeling is the way to teach them to become “smart.” What is data labeling? So, let’s deal with how this process happens. Source: GitHub.

Machine Learning 52

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Cloudera

DECEMBER 14, 2020

We’ve seen organizations invest in big data solutions, and now, we’ve increasingly seen them want to build on that investment and move towards building a modern architecture that’ll help them leverage stream processing and streaming analytics. Cloudera Data Platform (CDP) is the new data cloud built for the enterprise.

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Process Kafka Government Big Data 70

Knowledge Hut

MARCH 28, 2024

This will give you an idea of how the programs are processed effectively. In this post, we will understand many core data structure concepts. What is Data Structure? A data structure is a method for organizing, processing, retrieving, & storing information. How are Data Structures Used?

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RandomTrees

DECEMBER 12, 2023

Synthetic data helps us better understand the object or scene getting observed. It’s also a prerequisite for building novel algorithms for computer vision systems, but this is just a general talk. Let’s find out more about synthetic data in detail. What Is Synthetic Data In Machine Learning And How To Generate It?

Datasets 52

Datasets Deep Learning Healthcare Algorithm 52

Knowledge Hut

FEBRUARY 29, 2024

Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. Learning Data Visualization To discover hidden truth or information on business problem, data needs to be viewed properly.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

Towards Data Science

AUGUST 29, 2023

Data Quality Chronicles Missing data, missing mechanisms, and missing data profiling Missing Data prevents data scientists to see the entire story the data has to tell. Sometimes, even the smallest pieces of information can provide a completely unique view of the world.

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Knowledge Hut

DECEMBER 21, 2023

Why Cloud Computing is Important for Data-driven Business? The Cloud computing is crucial for data-driven businesses because it provides scalable and cost-effective ways to store and process huge amounts of data. It also includes an evolutionary algorithm for future improvement.

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Snowflake

DECEMBER 6, 2023

This issue, and similar issues I’ve watched loved ones manage in the past, piqued my interest in healthcare data as a whole, particularly whole-person data. Healthcare data can and should serve as a holistic, actionable tool that empowers caregivers to make informed decisions in real time. Not for lack of caring!

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Data Engineering Podcast

MAY 15, 2022

Summary Industrial applications are one of the primary adopters of Internet of Things (IoT) technologies, with business critical operations being informed by data collected across a fleet of sensors. Can you describe what Vopak is and what kinds of information you rely on to power the business?

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Knowledge Hut

MAY 31, 2023

Artificial intelligence (AI) projects are software-based initiatives that utilize machine learning, deep learning, natural language processing, computer vision, and other AI technologies to develop intelligent programs capable of performing various tasks with minimal human intervention.

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Knowledge Hut

JANUARY 11, 2024

A famous example in this sector is the unicorn '' Airbnb '', a startup that focussed on data science early to grow and adapt to the market faster. This company witnessed a 43000 percent hypergrowth in as little as five years using data science. BioTech How AstraZeneca harnesses data for innovation in medicine.

Data Science 98

Data Science Transportation Hospitality Banking 98

Knowledge Hut

MARCH 28, 2024

Software metrics encompass a variety of measures that assess the quality, performance, and efficiency of software development processes and products. They serve as critical indicators that help teams to identify areas of improvement, make informed decisions, and enhance productivity. What are Software Metrics in Software Engineering?

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Knowledge Hut

JANUARY 23, 2024

It's like the hidden dance partner of algorithms and data, creating an awesome symphony known as "Math and Data Science." " So, get ready for a fun ride in this blog as we explore the fascinating world of math in data science. Data Visualization: Ever been captivated by a visually stunning graph?

Data Science 52

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Databand.ai

JULY 6, 2023

These anomalies can significantly impact data analysis, leading to incorrect or misleading insights. Unintentional anomalies are data points that deviate from the norm due to errors or noise in the data collection process. These anomalies can distort the dataset, making it challenging to derive accurate insights.

Datasets 52

Datasets Algorithm Machine Learning Data Analysis 52

AltexSoft

MAY 27, 2022

A large hospital group partnered with Intel, the world’s leading chipmaker, and Cloudera, a Big Data platform built on Apache Hadoop , to create AI mechanisms predicting a discharge date at the time of admission. The built-in algorithm learns from every case, enhancing its results over time. Data preparation for LOS prediction.

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Knowledge Hut

JANUARY 19, 2024

Entering the world of data science is a strategic move in the 21st century, known for its lucrative opportunities. With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. Recognizing the growing need for data scientists, institutions worldwide are intensifying efforts to meet this demand.

Data Science 52

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ProjectPro

NOVEMBER 30, 2021

The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data. When working on real-time business problems, data scientists build models using various Machine Learning or Deep Learning algorithms.

Process 52

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Databand.ai

JUNE 8, 2023

By implementing an observability pipeline, which typically consists of multiple technologies and processes, organizations can gain insights into data pipeline performance, including metrics, errors, and resource usage. This ensures the reliability and accuracy of data-driven decision-making processes.

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Knowledge Hut

JULY 28, 2023

Parameters Machine Learning (ML) Deep Learning (DL) Feature Engineering ML algorithms rely on explicit feature extraction and engineering, where human experts define relevant features for the model. DL models automatically learn features from raw data, eliminating the need for explicit feature engineering. What is Machine Learning?

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

Knowledge Hut

JANUARY 24, 2024

In today's digital age, where information permeates every corner of our lives, the role of a data scientist bears a striking resemblance to that of a modern-day explorer. What Does a Data Scientist Do Data scientists are highly skilled professionals specializing in the art of extracting valuable insights from data.

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Database-centric Data Science Machine Learning Datasets 52

Monte Carlo

MARCH 18, 2024

Data quality audits are a key way to ensure your business decisions are being informed by fresh, accurate, and up-to-date data. Table of Contents What are Data Quality Audits? A data quality audit is a step-by-step process to validate the accuracy and trustworthiness of your data.

Datasets 52

Datasets Data Pipeline BI Data 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. This is one of the major reasons behind the popularity of data science. An exploratory study of the given data set.

Data Engineering 98

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Cloudera

NOVEMBER 19, 2020

To use such tools effectively, though, government organizations need a consolidated data platform–an infrastructure that enables the seamless ingestion and integration of widely varied data, across disparate systems, at speed and scale. However, this rapid scaling up of data across government agencies brings with it new challenges.

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Knowledge Hut

JULY 26, 2023

Veracity meaning in big data is the degree of accuracy and trustworthiness of data, which plays a pivotal role in deriving meaningful insights and making informed decisions. This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes.

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Big Data Data Cleanse Retail Healthcare 52

AltexSoft

APRIL 12, 2022

In our post, we give an informative explanation of responsible AI, its principles, and the approaches to ensure AI projects are implemented with responsibility in mind. An ML model is an algorithm (e.g., To enable algorithm fairness, you can: research biases and their causes in data (e.g., Source: SMBC Comics.

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