Dibyajit Kanungo

A fresher in Data Science field having knowledge of predictive modeling, data processing and data mining algorithms as well as scripting languages including Python. Created data visualization graphics, translating complex data sets into comprehensive visual representations. Identified, analyzed and interpreted trends in complex data sets using supervised and unsupervised learning techniques.

• Worked with structured and unstructured data from various
  sources, such as databases to support decision-making
  processes.
• Used machine learning tools to select features, create and
  optimize classifiers.
• Did Processing, cleaning, and validating the integrity of data
  for analysis
• Developed prediction systems and machine learning
  algorithms
• Created Dashboards using Tableau

• Employee of the month- August 2019, October 2019
• Star Performer- June 2018, July 2018, February 2019

• PYTHON & ITS LIBRARIES FOR DATA SCIENCE
• DATA ANALYSIS USING SQL
• QUANTITATIVE RESEARCH & STATISTICS IN DATA SCIENCE
• MACHINE LEARNING FOR DATA SCIENCE & ANALYTICS
• Business Analysis with Tableau
• Advanced JAVA
• Core JAVA

Name: Covid Health Care
Role: Predict the different levels of Covid disease and creating Dashboard
Libraries used: Pandas,Numpy, MatplotLib, Seaborn Algorithm Used : KNN, SVM, Random Forest Classifier, Decision Tree Classifier
Outcome: We can see that if our K value is less than 3, we get an
accuracy of more than 75%, but if we move to 4 the accuracy
significantly drops to 71%. So the ideal choice would a K value of
either 2 or 3.

On applying SVM and Random Forest Classifier, the accuracy is about 70%. We get an accuracy of about 72% by using the Decision Tree Classifier.