top data science tools in 2023

Top Data
Science Tools
in 2023
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Table Of Content
1. Google Analytics
2. Microsoft Excel
3. Apache Spark
4. Tensor flow
5. BigML
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Google Analytics
A tool offered by Google called Google
Analytics is widely used to monitor website
user activity. You may analyze the visitor
statistics on your website with the help of the
Google Analytics tool. The primary tool for
traffic control in all areas is Google Analytics.
Nearly all the content you publish online may
be tracked and kept an eye on in your
dashboard.
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Microsoft Excel
A spreadsheet is a computer program used to
add, display, analyze, organize, and work
with data in rows and columns. It is the most
widely used application for data
visualization, analytics, and accounting. To
put it another way, spreadsheets are gridbased,
scaleable files used to collect data and
carry out calculations. Spreadsheets are used
by people all around the world to build tables
for both personal and professional purposes.
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Apache Spark
Big data workloads are processed
using Apache Spark, an opensource
distributed processing
engine. It uses efficient query
execution and in-memory caching
for quick analytic queries against
any data size.
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Tensor flow
An open-source software library is
TensorFlow. TensorFlow was initially
created by researchers and engineers
working on the Google Brain Team
within Google's Machine Intelligence
research organization to conduct deep
learning and machine learning
research. Still, the system is versatile
enough to be used in a variety of other
domains as well.
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BigML
It is simple to solve and automate
Classification, Regression, Time Series
Forecasting, Cluster Analysis, Anomaly
Detection, Association Discovery, and Topic
Modeling issues with the help of BigML, a
consumable, programmable, and scalable
Machine Learning platform.
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