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What is difference between data science and Machine Learning

Basic Concept of data science and machine learning

Data Science is a field that is a combination of statistical methods, modeling techniques, and programming knowledge. On the one hand, a data scientist has to analyze the data to get the hidden insights and then apply the various algorithms to create a Machine Learning model.

Machine Learning is a subset of AI where the machine is trained to learn from it’s past experience. The past experience is developed through the data collected. Then it combines with algorithms such as Naïve Bayes, Support Vector Machine(SVM) to deliver the final results.

The key objective of machine learning is to empower computers to learn automatically without requiring ongoing human assistance or churning



Helps the marketing and sales area

Data-driven Marketing is a universal term nowadays.
The reason is simple: only with data, we can offer solutions, communications, and products that are genuinely in line with customer expectations and needs.the entire customer journey map considering all the touchpoints your customer had with your brand? This is possible with Data Science.

Enhance Data security.

The data scientists work on fraud prevention systems, for example, to keep your company’s customers safer. On the other hand, he can also study recurring patterns of behavior in a company’s systems to identify possible architectural flaws.

Helps to clarify complex data

When we want to cross different data to understand the business data science comes as great solutiion
and it makes market better.Depending on the tools we use to collect data, we can mix data from “physical” and virtual sources for better visualization.

It confirms real-time intelligence

The data scientist can work with RPA professionals to identify the different data sources of their business and create automated dashboards, which search all this data in real-time in an integrated manner.

Increase Business forecast

With the help of the data scientist, it is possible to use technologies such as Machine Learning and Artificial Intelligence to work with the data that the company has and, in this way, carry out more precise analyses of what is to come.


Automation of Everything

Machine Learning is responsible for cutting the workload and time. By automating things we let the algorithm do the hard work for us. Automation is now being done almost everywhere. The reason is that it is very reliable. Also, it helps us to think more creatively.

Wide range of applications

Machine Learning is used in every industry these days, for example, from Defense to Education. Companies generate profits, cut costs, automate, predict the future, analyze trends and patterns from the past data, and many more. Applications like GPS Tracking for traffic, Email spam filtering, text prediction, spell check and correction, etc are a few used widely these days

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What is difference between data science and Machine Learning


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