Data Preparation and Raw Data in Machine Learning
KDnuggets
JULY 12, 2022
In this article, I will describe the data preparation techniques for machine learning.
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Audio Analysis With Machine Learning: Building AI-Fueled Sound Detection App
AltexSoft
MAY 12, 2022
Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. But first, let’s go over the basics: What is the audio analysis, and what makes audio data so challenging to deal with.
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Tableau Prep Builder: Streamline Your Data Preparation Process
Edureka
JULY 5, 2024
Tableau Prep is a fast and efficient data preparation and integration solution (Extract, Transform, Load process) for preparing data for analysis in other Tableau applications, such as Tableau Desktop. simultaneously making raw data efficient to form insights.
?Data Engineer vs Machine Learning Engineer: What to Choose?
Knowledge Hut
JUNE 20, 2023
A novice data scientist prepared to start a rewarding journey may need clarification on the differences between a data scientist and a machine learning engineer. Many people are learning data science for the first time and need help comprehending the two job positions.
Data Labeling in Machine Learning: Process, Types, and Best Practices
AltexSoft
DECEMBER 21, 2021
When people hear about artificial intelligence, deep learning, and machine learning , many think of movie-like robots that resemble or even outperform human intelligence. Others believe that such machines simply consume information and learn from it by themselves. What is data labeling? Source: GitHub.
Document Classification With Machine Learning: Computer Vision, OCR, NLP, and Other Techniques
AltexSoft
NOVEMBER 17, 2021
So businesses employ machine learning (ML) and Artificial Intelligence (AI) technologies for classification tasks. Namely, we’ll look at how rule-based systems and machine learning models work in this context. It requires extracting raw data from claims automatically and applying NLP for analysis.
Future Proof Your Career With Data Skills
Knowledge Hut
MAY 1, 2024
It is important to make use of this big data by processing it into something useful so that the organizations can use advanced analytics and insights to their advant age (generating better profits, more customer-reach, and so on). These steps will help understand the data, extract hidden patterns and put forward insights about the data.
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Data Vault on Snowflake: Feature Engineering and Business Vault
Snowflake
MARCH 30, 2023
A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.
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Power BI Skills in Demand: How to Stand Out in the Job Market
Knowledge Hut
SEPTEMBER 26, 2023
Workspace is the platform where power BI developers create reports, dashboards, data sets, etc. Dataset is the collection of raw data imported from various data sources for the purpose of analysis. DirectQuery and Live Connection: Connecting to data without importing it, ideal for real-time or large datasets.
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Enabling The Full ML Lifecycle For Scaling AI Use Cases
Cloudera
DECEMBER 17, 2020
When it comes to machine learning (ML) in the enterprise, there are many misconceptions about what it actually takes to effectively employ machine learning models and scale AI use cases. Accelerating the Full Machine Learning Lifecycle With Cloudera Data Platform.
The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure
DataKitchen
JULY 27, 2023
You can use it for big data analytics and machine learning workloads. Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. It provides data prep, management, and enterprise data warehousing tools.
Power BI System Requirements Specification of 2023
Knowledge Hut
OCTOBER 4, 2023
While the numbers are impressive (and a little intimidating), what would we do with the raw data without context? The tool will sort and aggregate these raw data and transport them into actionable, intelligent insights. If this trend continues to evolve, it will nearly double by 2025.
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Top Data Cleaning Techniques & Best Practices for 2024
Knowledge Hut
JANUARY 25, 2024
Data cleaning is like ensuring that the ingredients in a recipe are fresh and accurate; otherwise, the final dish won't turn out as expected. It's a foundational step in data preparation, setting the stage for meaningful and reliable insights and decision-making. Here's why cleaning data is super important: 1.
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How To Switch To Data Science From Your Current Career Path?
Knowledge Hut
NOVEMBER 27, 2023
Developing technical skills is essential, starting with foundational knowledge in mathematics, including calculus and linear algebra, which underpin machine learning and deep learning concepts. Through the article, we will learn what data scientists do, and how to transits to a data science career path.
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An AI Chat Bot Wrote This Blog Post …
DataKitchen
DECEMBER 9, 2022
DataOps involves collaboration between data engineers, data scientists, and IT operations teams to create a more efficient and effective data pipeline, from the collection of raw data to the delivery of insights and results. Overall, DataOps is an essential component of modern data-driven organizations.
How to Build a Data Pipeline in 6 Steps
Ascend.io
JANUARY 2, 2024
The key differentiation lies in the transformational steps that a data pipeline includes to make data business-ready. Ultimately, the core function of a pipeline is to take raw data and turn it into valuable, accessible insights that drive business growth. analytics, machine learning)? cleaning, formatting)?
ESG Report Finds Ascend Increases Data Engineering Productivity By 700%
Ascend.io
AUGUST 16, 2023
The collection and preparation of data used for analytics are achieved by building data pipelines that ingest raw data and transform it into useful formats leveraging cloud data platforms like Snowflake, Databricks, and Google BigQuery.
Business Intelligence vs. Data Mining: A Comparison
Knowledge Hut
JUNE 28, 2023
Structured data from databases, data warehouses, and operational systems. Goal Extracting valuable information from raw data for predictive or descriptive purposes. Methods and Techniques Machine learning, statistical analysis, clustering, classification, association rule mining, etc.
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Data testing tools: Key capabilities you should know
Databand.ai
AUGUST 30, 2023
Data testing tools: Key capabilities you should know Helen Soloveichik August 30, 2023 Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing and maintaining data quality. There are several types of data testing tools.
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What is Data Extraction? Examples, Tools & Techniques
Knowledge Hut
JANUARY 30, 2024
In today's world, where data rules the roost, data extraction is the key to unlocking its hidden treasures. As someone deeply immersed in the world of data science, I know that raw data is the lifeblood of innovation, decision-making, and business progress. What is data extraction?
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12 Must-Have Skills for Data Analysts
Knowledge Hut
JUNE 16, 2023
Analyzing data with statistical and computational methods to conclude any information is known as data analytics. Finding patterns, trends, and insights, entails cleaning and translating raw data into a format that can be easily analyzed. They then arrange the data in a suitable format that is simple to understand.
Natural Language Processing: A Guide to NLP Use Cases, Approaches, and Tools
AltexSoft
AUGUST 25, 2021
Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech. NLP techniques open tons of opportunities for human-machine interactions that we’ve been exploring for decades. Machine learning-based NLP — the basic way of doing NLP.
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Data Testing Tools: Key Capabilities and 6 Tools You Should Know
Databand.ai
AUGUST 30, 2023
Data testing tools are software applications designed to assist data engineers and other professionals in validating, analyzing, and maintaining data quality. There are several types of data testing tools.
Data Cleanse 52
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Deep Learning in Production for Predicting Consumer Behavior
Zalando Engineering
MARCH 21, 2017
At Zalando adtech lab in Hamburg, machine learning drives many of our production systems to build great user experiences. Instead, we can focus on building a flexible and versatile model that can be easily extended to new types of input data and applied to a variety of prediction tasks.
Data Mining Functionalities: Meaning, Frameworks & Examples
Edureka
JANUARY 23, 2023
The use of data by companies to understand business patterns and predict future occurrences has been on the rise. With the availability of new technologies like machine learning, it has become easy for experts to analyse vast quantities of information to find patterns that will help establishments make better decisions.
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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly
ProjectPro
FEBRUARY 8, 2023
But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.
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Data Science Prerequisites 2022: Skills Required
U-Next
SEPTEMBER 9, 2022
Making judgments and predictions via Machine Learning, prescriptive analytics, and predictive causal analysis is the major application of Data Science. What is Data Science? . They gather, purge, and arrange data that can eventually be leveraged to make business growth strategies. . Machine Learning .
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A Brief Overview of HR Analytics: Descriptive, Predictive, And Prescriptive
U-Next
SEPTEMBER 28, 2022
Let’s learn the types of HR Analytics one by one: . Descriptive HR Analytics meaning describes or summarizes raw data to make it human-interpretable. Data preparation occurs before the analysis stage and is crucial to ensuring correctness; it is also one of the most time-consuming tasks for the analyst. .
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Semi-Supervised Learning, Explained with Examples
AltexSoft
MARCH 18, 2022
Machine learning is no exception. You’ve probably heard of two main ML techniques — supervised and unsupervised learning. The mixture of two gave birth to the happy medium known as semi-supervised learning. Supervised vs unsupervised vs semi-supervised machine learning in a nutshell.
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Top 15 Power BI Project Ideas
Knowledge Hut
OCTOBER 27, 2023
Microsoft created Power BI, a business analytics tool that enables users to visualize and analyze data from various sources quickly and interactively. It provides a wide range of features and functionalities, including data preparation, data modeling, data visualization, and collaboration tools.
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Power BI Developer Roles and Responsibilities [2023 Updated]
Knowledge Hut
OCTOBER 30, 2023
The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. The capacity to translate business requirements into data visualization solutions. Who is a Power BI Developer?
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Case Study: The Path to Better Pollution Forecasting Goes Through Nested JSON
Rockset
MARCH 19, 2019
“With Rockset, I don’t have to worry about data being typed or formatted in a way I didn’t anticipate, and I don’t have to modify my code every time the schema changes. Rockset just sucks in all the raw data and makes it accessible using SQL, so it's faster and easier to develop on the data.”
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100+ Big Data Interview Questions and Answers 2023
ProjectPro
JANUARY 31, 2023
Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.
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Top Business Intelligence Platforms of 2024 [with Features]
Knowledge Hut
DECEMBER 26, 2023
Learn all about Business Intelligence and Visualization training and earn business intelligence certifications. Business intelligence (BI) is the collective name for a set of processes, systems, and technologies that turn raw data into knowledge that can be used to operate enterprises profitably. Enroll now!
Snowflake Architecture and It's Fundamental Concepts
ProjectPro
JANUARY 31, 2022
Snowflake Features that Make Data Science Easier Here are three Snowflake attributes that make running successful data science projects easier for businesses- 1. Centralized Source of Data When training machine learning models, data scientists must consider a wide range of data.
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Big Data Analytics: How It Works, Tools, and Real-Life Applications
AltexSoft
MAY 14, 2021
Modern technologies allow gathering both structured (data that comes in tabular formats mostly) and unstructured data (all sorts of data formats) from an array of sources including websites, mobile applications, databases, flat files, customer relationship management systems (CRMs), IoT sensors, and so on. The Ginger.io
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20+ Data Engineering Projects for Beginners with Source Code
ProjectPro
AUGUST 24, 2021
Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Machine Learning web service to host forecasting code.
Innovation in Big Data Technologies aides Hadoop Adoption
ProjectPro
APRIL 27, 2016
Pig Hadoop dominates the big data infrastructure at Yahoo as 60% of the processing happens through Apache Pig Scripts. Today, Hive is used at Facebook to store more than 2 petabytes of uncompressed data and regularly loads more than 15 terabytes of data daily.
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Top 6 Big Data and Business Analytics Companies to Work For in 2023
ProjectPro
MAY 20, 2015
It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.
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Data Analyst Interview Questions to prepare for in 2023
ProjectPro
DECEMBER 22, 2016
If you are aspiring to be a data analyst then the core competencies that you should be familiar with are distributed computing frameworks like Hadoop and Spark, knowledge of programming languages like Python, R , SAS, data munging, data visualization, math , statistics , and machine learning.
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Understanding the 4 Fundamental Components of Big Data Ecosystem
U-Next
SEPTEMBER 23, 2022
In Big Data systems, data can be left in its raw form and subsequently filtered and structured as needed for specific analytical needs. In other circumstances, it is preprocessed using data mining methods and data preparation software to prepare it for ordinary applications. . Ingestion .
How to Become a Big Data Engineer in 2023
ProjectPro
SEPTEMBER 26, 2021
Big Data Engineer performs a multi-faceted role in an organization by identifying, extracting, and delivering the data sets in useful formats. A Big Data Engineer also constructs, tests, and maintains the Big Data architecture. Your organization will use internal and external sources to port the data.
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Top 20 Data Analytics Projects for Students to Practice in 2023
ProjectPro
JUNE 24, 2021
Microsoft Excel: A successful Excel spreadsheet helps to organize raw data into a more readable format. With more complex data, Excel allows customization of fields and functions that can make calculations based on the data in the excel spreadsheet. Topic modelling can also be used to classify large datasets of emails.
20 Solved End-to-End Big Data Projects with Source Code
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. There are open data platforms in several regions (like data.gov in the U.S.).
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