Knowledge Hut

DECEMBER 28, 2023

Hadoop is a popular open-source framework that stores and processes large datasets in a distributed manner. Organizations are increasingly interested in Hadoop to gain insights and a competitive advantage from their massive datasets. Hadoop can store data and run applications on cost-effective hardware clusters.

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ProjectPro

JANUARY 15, 2021

Undoubtedly, everyone knows that the only best way to learn data science and machine learning is to learn them by doing diverse projects. Table of Contents What is a dataset in machine learning? Why you need machine learning datasets? Where can I find datasets for machine learning? Why you need machine learning datasets?

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Datasets Machine Learning Retail Banking 40

Knowledge Hut

DECEMBER 21, 2023

With the help of these tools, analysts can discover new insights into the data. Hadoop helps in data mining, predictive analytics, and ML applications. Why are Hadoop Big Data Tools Needed? Features: HDFS incorporates concepts like blocks, data nodes, node names, etc. The files stored in HDFS are easily accessible.

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Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

DECEMBER 29, 2023

Data Mining Data science field of study, data mining is the practice of applying certain approaches to data in order to get useful information from it, which may then be used by a company to make informed choices. It separates the hidden links and patterns in the data.

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ProjectPro

JULY 21, 2021

Upskill yourself for your dream job with industry-level big data projects with source code NLP Projects Idea #2 Conversational Bots: ChatBots As we mentioned at the beginning of this blog, most tech companies are now utilizing conversational bots, called Chatbots to interact with their customers and resolve their issues.

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Coding Project Deep Learning Algorithm 52

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

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ETL Tools Database-centric Data Mining Data Cleanse 52

ProjectPro

AUGUST 24, 2021

. :) But before you start data engineering project ideas list, read the next section to know what your checklist for prepping for data engineering role should look like and why. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

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Data Engineering Data Engineer Coding Project 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. Kicking off a big data analytics project is always the most challenging part.

Big Data 52

Big Data Coding Project Hadoop 52

Knowledge Hut

APRIL 19, 2023

This article will help you understand what data aggregation is, its levels, examples, process, tools, use cases, benefits, types, and differences between data aggregation and data mining. If you would like to learn more about different data aggregation techniques check out a Data Engineer certification program.

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Process Data Mining Aggregated Data Portfolio 59

Knowledge Hut

DECEMBER 22, 2023

Data analytics, data mining, artificial intelligence, machine learning, deep learning, and other related matters are all included under the collective term "data science" When it comes to data science, it is one of the industries with the fastest growth in terms of income potential and career opportunities.

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Knowledge Hut

JANUARY 19, 2024

Embracing data science isn't just about understanding numbers; it's about wielding the power to make impactful decisions. Imagine having the ability to extract meaningful insights from diverse datasets, being the architect of informed strategies that drive business success. That's the promise of a career in data science.

Data Science 52

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Knowledge Hut

FEBRUARY 7, 2023

Aside from that, users can also generate descriptive visualizations through graphs, and other SAS versions provide reporting on machine learning, data mining, time series, and so on.  DATA Step: The data step includes all SAS statements, beginning with line data and ending with line datalines.

Data Science 52

Data Science Datasets SQL Data Mining 52

ProjectPro

OCTOBER 29, 2021

How then is the data transformed to improve data quality and, consequently, extract its full potential? Data Preprocessing to the rescue! Table of Contents What is Data Preprocessing? This is why we will get back to the über important topic of improving data quality by preprocessing in the later section.

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

Knowledge Hut

JUNE 15, 2023

As each issue gets defined dedicatedly, it will be convenient for every team member to read, reuse and test the code. So, focus on enhancing modularity, and your data management will become utterly convenient. Every time the new datasets get extracted, make sure you segregate them into modules based on their use or category.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

DECEMBER 26, 2023

It is a group of resources and services for turning data into usable knowledge and information. Descriptive analytics, performance benchmarking, process analysis, and data mining fall under the business intelligence (BI) umbrella. Once the budget reports are authorized, users can transfer the budget data to ERP.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

ProjectPro

AUGUST 16, 2021

Evolution of Machine Learning Applications in Finance : From Theory to Practice Music Recommendation System on KKbox Dataset The project aims at predicting if a user will listen to a song again in a period. KKbox provides a dataset for the project in user-song pairs and the first recorded listening time, along with song and user details.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

Knowledge Hut

JULY 7, 2023

The practice of integrating code changes into a common repository and pushing code changes to production in small, periodic batches is known as continuous integration and deployment (CI/CD). Similarly, an AI-powered testing tool might build test cases and analyze test results automatically to discover areas for improvement.

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Software Engineer Software Engineering Engineering Data Mining 52

Knowledge Hut

NOVEMBER 28, 2023

Hence, learning and developing the required data engineer skills set will ensure a better future and can even land you better salaries in good companies anywhere in the world. After all, data engineer skills are required to collect data, transform it appropriately, and make it accessible to data scientists.

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Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

DECEMBER 26, 2023

R for Data Science – By Hadley Wickham and Garret Grolemund Source: amazon.com R is a programming language also used in many Data Science applications. This book will help you in the following ways:- You will learn the basics of coding with the R programming language.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

ProjectPro

APRIL 20, 2017

Having multiple hadoop projects on your resume will help employers substantiate that you can learn any new big data skills and apply them to real life challenging problems instead of just listing a pile of hadoop certifications. Data Analyst Responsibilities-What does a data analyst do? Analyse log files in HIVE.

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Hadoop Big Data Coding Project 40

Grouparoo

NOVEMBER 16, 2021

Loading is the process of warehousing the data in an accessible location. The difference here is that warehoused data is in its raw form, with the transformation only performed on-demand following information access. One of the leaders in the space focused on data transforms is dbt.

Data Mining 52

Data Mining Raw Data ETL Tools Unstructured Data 52

ProjectPro

DECEMBER 21, 2021

Also, you will find many Python code snippets available online that will assist you in the same. Here are a few beginner-friendly machine learning projects with source code that you might want to explore- 1. The Rossmann Stores dataset is one of the most popular datasets used by Data Science beginners.

Machine Learning 52

Machine Learning Engineering Algorithm Computer Science 52

ProjectPro

DECEMBER 7, 2021

Consider these free data analyst portfolio platforms if you're just getting started: Github : GitHub, an open-source community of 56 million developers, is one such popular choice for hosting your portfolio for free. In reality, a technical screening using SQL is a regular part of data analyst interviews.

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Portfolio Building Data Mining Data Analysis 52

Knowledge Hut

JANUARY 22, 2024

Check out the Data Science course fee to start your journey. Why is Data Science So Important? Data is not useful until it is transformed into valuable information. Mining large datasets containing structured and unstructured data and identifying hidden patterns to gain actionable insights are two main tasks in data science.

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Data Science Banking Big Data Insurance 52

ProjectPro

JUNE 18, 2021

Get Closer To Your Dream of Becoming a Data Scientist with 70+ Solved End-to-End ML Projects Python is a simple and easy-to-learn programming language. It requires much fewer lines of code than other programming languages to perform the same operations. Java for Data Science - Should data scientists learn Java?

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Java Data Science Python Programming Language 52

ProjectPro

OCTOBER 28, 2021

List of Prerequisites for Machine Learning Basic Mathematical Prerequisites for Machine Learning Linear Algebra Prerequisites for Machine Learning Is Coding required for Machine Learning? It simplifies complex problems by making probabilistic predictions for specific parameters in the dataset. Is Coding required for Machine Learning?

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Machine Learning Programming Language Datasets Python 52

ProjectPro

OCTOBER 16, 2021

Hands-On Machine Learning with Scikit-learn and TensorFlow: The Introduction Scikit-learn is the go-to machine learning library for Data Scientists who work with Python programming language. It contains codes to support the implementation of machine learning algorithms in Python. for predicting the status of a loan application.

Machine Learning 52

Machine Learning Deep Learning Datasets Algorithm 52

ProjectPro

OCTOBER 26, 2021

TensorFlow clusters together machine learning and deep learning models and renders them through large datasets to train these models to think and create sensible outcomes on their own. It helps in implementing predictive analytics with mathematics to make decisions based on granular data. It is Spark's fundamental data structure.

Machine Learning 52

Machine Learning Programming Language Healthcare Deep Learning 52

Knowledge Hut

JANUARY 18, 2024

Wider Adoption by Business Users The increasing adoption of data analytics by business users is driving significant changes in the data analytics industry. Historically, data analytics was a highly technical field requiring specialized skills and expertise.

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Data Analytics Healthcare Machine Learning Algorithm 52

ProjectPro

JUNE 24, 2021

Here is the list of key technical skills required for analytics job roles which can also be acquired by students or professionals from a non- technical background - SQL : Structured Query Language is required to query data present in databases. Even data that has to be filtered, will have to be stored in an updated location.

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Data Analytics Project Insurance Hadoop 40

ProjectPro

JANUARY 19, 2022

Azure Data Engineer Job Description | Accenture Azure Certified Data Engineer Azure Data Engineer Certification Microsoft Azure Projects for Practice to Enhance Your Portfolio FAQs Who is an Azure Data Engineer? This is where the Azure Data Engineer enters the picture.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

U-Next

SEPTEMBER 19, 2022

You may rapidly search for critical insights and datasets inside your data using the Quick Insights option. Create a live or non-live connectivity to on-premises data sources like SQL Server and access information through data gateways using a secure channel. Below are some most used data sources.

BI 40

BI Business Intelligence Datasets Retail 40

U-Next

DECEMBER 2, 2022

Data science is a field of study that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. It is widely used in the data science community and is the language of choice for many data scientists.

Machine Learning 40

Machine Learning Data Science Programming Language Data Mining 40

ProjectPro

DECEMBER 22, 2016

We have collected a library of solved Data Science use-case code examples that you can find here. Data Analyst Interview Questions and Answers 1) What is the difference between Data Mining and Data Analysis? Data analysis begins with a question or an assumption. Data analysis involves data cleaning.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

ProjectPro

AUGUST 5, 2021

You can use the Resume Dataset available on Kaggle to build this model. This dataset contains only two columns — job title and the candidate’s resume information. The data is present in the form of text and needs to be pre-processed. Dataset: Kaggle Resume Dataset 2. Python Package: GluonNLP 4.

Project 52

Project Datasets Deep Learning Machine Learning 52

ProjectPro

JANUARY 25, 2022

Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. Because of its interoperability, it is the best framework for processing large datasets. Easy Processing- PySpark enables us to process data rapidly, around 100 times quicker in memory and ten times faster on storage.

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Big Data Data Process Process Kafka 52

ProjectPro

JUNE 22, 2021

These will allow you to access things from your wardrobe just by a single tap on your phone. Binary Classification Machine Learning This type of classification involves separating the dataset into two categories. Imbalanced Classification Example: Detecting fraudulent transactions through a credit card in a transaction dataset.

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Machine Learning Algorithm Datasets Project 72