Knowledge Hut

OCTOBER 5, 2023

The organizations can even ask the experts to help them create their systems using cloud and/or legacy components. AWS Big Data specialists should thoroughly understand programming languages such as C and C++, technological applications, and cloud environments. Zenith Systems INR 34.2 – 43.7L

Big Data 52

Big Data AWS Certification Amazon Web Services 52

Knowledge Hut

JANUARY 19, 2024

Business Intelligence Transforming raw data into actionable insights for informed business decisions. Programming Languages Delving into programming languages such as R and Python, along with exposure to database languages like SQL. Paving the way for creating intelligent systems.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

JANUARY 16, 2024

In traditional machine learning, data combined with statistical tools generate predictions that offer practical insights for decision-making. Machine learning drives advancements in image and speech recognition, Natural Language Processing (NLP), recommendation systems, and applications like fraud detection.

Machine Learning 98

Machine Learning Engineering Programming Language Algorithm 98

ProjectPro

SEPTEMBER 27, 2021

Covariance In Finance and Portfolio Management Correlation vs. Covariance: Machine Learning Project Ideas FAQs Correlation vs. Covariance We will now explore the two statistical concepts often used together to perform exploratory data analysis over a dataset. How to find correlations among feature variables in R?

Datasets 52

Datasets Finance Portfolio Banking 52

ProjectPro

SEPTEMBER 26, 2021

Senior Big Data Engineer Salary, The average salary of a Big Data Engineer with over 8 to 10 years of experience is around $120K. The senior-level roles require expert knowledge and skills in complex data analysis and programming. How much is the salary of a big data engineer?

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

FEBRUARY 24, 2016

Whether it is preparing perfectly clean data for a model, writing reusable code, building a resilient data pipeline, building a reproducible machine learning pipeline , or revisiting high-performing systems- senior data scientists have it all. According to PayScale, the average senior data scientist salary is $128,225.

Hadoop 40

Hadoop Data Science Computer Science R (Programming) 40

Knowledge Hut

JANUARY 24, 2024

Programming Support Compared to Power BI, Tableau integrates much better with R. Power BI supports Data Analysis Expression and the M language for data manipulation and modeling. Data Visualization Tableau allows its users to customize dashboards specifically for devices.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

ProjectPro

DECEMBER 14, 2021

Data insights, improved quality, and correct data condensed in a single document have become more critical. Companies interested in harnessing data should invest in a business intelligence system. Customer Churn Analysis 2. Product Sales Data Analysis 3. Marketing Campaign Insights Analysis 4.

BI 52

BI Project Business Intelligence Datasets 52

ProjectPro

JANUARY 20, 2022

The ML engineer would be responsible for working on various Amazon projects, such as building a product recommendation system or, a retail price optimization system. The ML Engineer will need to collaborate directly with live production systems and product teams to offer ML solutions within the Twitter tech stack.

Machine Learning 52

Machine Learning Deep Learning Algorithm Programming Language 52

ProjectPro

AUGUST 11, 2016

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

Knowledge Hut

FEBRUARY 12, 2023

Mid-Level Jobs Most companies consider data science professionals with 2 to 6 years of experience for mid-level jobs and a suitable certification. The job expects the candidates to possess in-depth knowledge of programming languages, statistical tools, data visualization, and applied mathematics.

Data Science 52

Data Science Computer Science Portfolio Certification 52

Knowledge Hut

FEBRUARY 7, 2023

A data science platform is software that includes a variety of technologies for machine learning, data science, and other advanced analytics projects. Typically, data science projects involve using an abundance of ls (eg. A Data Science certificate that trains you on these platforms are a great way to ensure better productivity.

Data Science 52

Data Science Google Cloud Programming Language AWS 52

ProjectPro

JANUARY 6, 2022

Pygal Learning Python for Data Analysis and Visualization FAQs Is matplotlib better than plotly? Which library is best for data visualization in Python? Why Use Python for Data Visualization? Python is a prevalent general-purpose programming language commonly used for data visualization in the data science community.

Python 52

Python Datasets Programming Language Data Science 52

ProjectPro

JUNE 17, 2015

The big data phenomenon is just incomplete without the use of popular NoSQL databases like MongoDB, Cassandra, HBase Neo4j, CouchDB, Riak and Redis. NoSQL database systems are developed to handle huge unstructured datasets across various commodity servers with no single point of failure. from the previous year.

Cloud Computing 40

Cloud Computing Big Data R (Programming) Big Data Skills 40

ProjectPro

NOVEMBER 30, 2021

In this project, you will build an automated price recommendation system using Mercari’s dataset to suggest prices to their sellers for different products based on the information collected. Project Idea: In this project, you will learn how a business analyst can use data analysis methods and help promote the growth of a business.

Business Analyst 52

Business Analyst Project Retail Datasets 52

ProjectPro

AUGUST 21, 2015

IBM has a nice, simple explanation for the four critical features of big data: a) Volume –Scale of data b) Velocity –Analysis of streaming data c) Variety – Different forms of data d) Veracity –Uncertainty of data Here is an explanatory video on the four V’s of Big Data 3.

Hadoop 40

Hadoop Big Data Metadata Java 40