DATA SCIENCE AND MACHINE LEARNING
DATA SCIENCE :
The first time that I heard about the term “Data Science” was when I was attending some webinar in 2017. Back then, I really thought that Machine Learning and Data Science were some kind of universal panacea for the world’s biggest problems.Well that is not the case.
In simpler terms, Data Science is a branch of study which involves obtaining meaningful insights from raw & unstructured data. The colossal amount of data is processed through programming, analytical & business skills.
Data Science is a multi- disciplinary field that uses scientific methods, processes, algorithms to produce knowledge & insights from structured & unstructured data. It utilises techniques & theories derived from many fields such as computer science, mathematics, statistics & information science.
Data science generally has a five-stage lifecycle that consists of:
- Capture: Data acquisition, data entry, signal reception, data extraction
- Maintain: Data warehousing, data cleansing, data staging, data processing, data architecture
- Process: Data mining, clustering/classification, data modeling, data summarization
- Communicate: Data reporting, data visualization, business intelligence, decision making
- Analyze: Exploratory/confirmatory, predictive analysis, regression, text mining, qualitative analysis.
There is a popular saying “your intelligence is only as strong as the data that backs it”, this explains the power of the data in human life. As per Forbes 2019 reports, internet data created per day is almost equal to 2.9 quintillion byte. A quintillion byte equals to one billion gigabytes. Every aspect of human life is transformed to data in many ways by the electronic equipment he/she handles daily. The increase in data generation is directly proportional to the development in the wearable devices, IoT, Tweets, mobile communications, etc., Google handles more than 60,000 searches per second, Twitter administer 0.5 million tweets per day, more than 160 million emails sent every day, these all accumulates into vast database ever known to the humankind. The concept of big data is getting bigger and bigger every second. An estimate of the global economic group states at the end of 2020, data flows will constitute 15 to 22 percent of the global GDP. The impact of data in the Indian economy is becoming vital day by day. At the end of 2030, 50 percent of the Indian economy will be constituted by the data-driven digital market.
The major hurdle in the digital markets is finding insights into data. Data abundance is making it difficult for organizations to get the right insights of data. Data science and data analytics come in handy to deal with unstructured raw data gathered by various sources. Data science is basically the study of a combination of mathematics, statistics, programming, and capturing data in ingenious ways, the activity of cleansing, and aligning the data. This is an umbrella of data manipulation techniques to extract information from data.
MACHINE LEARNING :
Machine Learning is an application that can make the system to give the output from the past experiences without being explicitly programmed.The primary aim is to allow the computers learn automatically without human assistance and adjust action accordingly.
Machine learning was first introduced by Arthur Samuel in 1959 in field of computer gaming and artificial intelligence (AI).
“ It gives computer the ability to learn without explicitly programmed”.
In today’s business scenario every business organization has a large amount of data. This data is handled by machine learning with the help of pattern recognition and finding out values from hidden data identification of hidden values business organization can work effectively.
Machine learning enables business to automate analysis. Machine learning has the capability to analyze superior data, scalability, and automation in knowledge of basic algorithm. A machine can learn from example and experience.
Application of machine learning:
1. Web search engine
2. Photo tagging application
3. Spam detector
4. Financial sector
5. Health care
6. Self organizing mapping used by Google map.
These are just my two cents on what data science and machine learning is. I hope it make sense to you so far. I'm still a learner, and merely a beginner in this field, and I expect to pick up a lot more and deeper understanding on this subject matter in the near future.
