Big Data and Machine Learning are very popular nowadays. However, there is no direct relation between Machine learning & big data. However, big data techniques can be used in machine learning. We will tell you the simple way to differentiate between both the fields. Usually, machine learning works with huge chunks of data and this is where big data comes into frame.
It is the science of algorithms and program which learn on their own. No human is needed after it is designed to make it better. Common application of machine learning includes:-
- Web Search
- Recommender System
- Add Placement
- Credit Scoring
- Fraud Detection
- Stock Trading
- Computer Vision
- Drug Decision
To put it simply, it is difficult for humans to create such models for every possible search or spam, so you make the machine intelligent enough to learn by itself. The process of converting the later part of data mining is known as machine learning. The term machine learning is self-explanatory. Machines itself learn to perform tasks that are not programmed specifically. Many techniques are undertaken into practice, like supervised clustering, regression, naïve Bayes, etc.
Data science is a broad concept that covers each and every aspect of data processing, not only statistical or algorithmic aspects. Thus we can say machine learning is a part of data science.
Data science includes:
- Data Integration
- Data Engineering
- Data Visualization
- Distributed Architecture
- Dash Board and BI
- Automatic Machine Learning
- Automated Data Driven decision
- Deployment in Production Mode
With the help of machine learning, data science makes a provision for data analysis, data preparation, and decision-making, like online learning and real-time testing. Data science combines data together derived from machine learning that provide solutions. Data science brings out the activity of taking ideas from basic Mathematics, Statistics and domain expertise.
Big Data Analytics
It studies the big data which helps to identify hidden patterns, market trends, consumer preferences, and other valuable information that helps organizations to form strategic business decisions.
With the help of big data analytics, scientists and data professionals examine huge amounts of structured data as well as unused data by deploying analytics and business intelligence.
With the help of special software and analytic systems of big data analytics, businesses benefit in following ways:
- New Product and Service: Big data analytics helps to understand consumer needs and preferences by giving more power to consumers and serving according to consumer needs. This helps to develop more products and services that fulfill customers’ needs.
- Faster Decision Making: With the help of “Hadoop,” organizations can examine data immediately. Decisions can be influenced on the basis of what they have experienced.
- Cost Efficiency: “Hadoop” and cloud-based analytics are big data analytics technologies at very effective costs when it comes to storing large data. This helps create effective ways of doing business.
In this article, you learned something about big data and machine learning. Both fields are huge and very interesting as well. Keep learning 🙂