DataScience Research

With the developing significance of data science and the continuous shortage of proper skillset, the job of the datascientists is to a great degree noteworthy today. For a considerable length of time, undertakings have incorporated a few people with business aptitude fit for crossing over any barrier among business and IT by discovering data-driven answers for business issues utilizing available self-benefit examination programming.

Data Science as a domain has turned out to be progressively imperative with the blast of examination, AI, machine learning, and huge data all through the work environment amid the previous quite a long while. It additionally mitigates the issue of business-IT arrangement that has existed since PCs were first used to take care of business issues.

Research Areas under Data Science: In this age of hyper-information, anything and everything is data. Data is in present days, considered as “ Digital Gold”. Data Science is an umbrella term which covers multiple sub-divisions which are Math, Statistics, Domain Expertise, Advanced Computing etc. In each area, there are numerous fields where research can be done. It would be quite an exaggerating term to mention as data science researchers as there are multiple domains and countless topics that come under the purview of data science.

Data Science Projects:

There are countless data science projects and the number is growing in an exponential way. In data science, Data mining research topics can also be incorporated. Few data science projects which have come across my mind and have been on the favorite list of the researchers are:

  • An Expert Clinical Decision Support System to Predict Disease Using Classification Techniques.
  • Chronic Kidney Disease Prediction on Imbalanced Data by Multilayer Perceptron
  • Application of Data Mining Methods in Diabetes Prediction
  • Predicting Depression Levels Using Social Media Posts
  • Implementing WEKA for medical data classification and early disease prediction
  • Emotion classification of YouTube videos
  • Sentiment analysis of the demonetization of economy
  • Comparison of applications for educational data mining in Engineering Education
  • Predicting Students Performance in Final Examination using Linear Regression and Multilayer Perceptron
  • Opinion Mining of News Headlines using SentiWordNet
  • A Novel Text Mining Approach Based on TF-IDF and Support Vector Machine for News Classification
  • Modifying Naive Bayes Classifier for Multinomial Text Classification
  • Improved Feature Extraction and Classification – Sentiment Analysis
  • Study of Machine Learning Algorithms for Special Disease Prediction using Principal of Component Analysis
  • Prediction of Heart Diseases Using Associative Classification
  • Data Analysts vs Data Scientists
  • The influence of extraction methods
  • Data Science and its Relationship to Big Data and Data-Driven Decision Making
  • The list is never-ending. From Statistics for Data Science to data mining, every area is a burgeoning field for researchers as Data Science is gobbling and encompassing across all the domains irrespective of the fields or the industry. Data science research topics are never exhausting list which will continue to grow every day due to a massive explosion of the dataset and the ever increasing demand for data science.