Sreyas institute of engineering and
Graduation – 60%
Operating systems: Windows
Machine learning: R/Python Modules
(NumPy, Pandas, Scikit Learn, Matplot Lib,
Stat models) and SPSS
Deep Learning: Tensor Flow, Keras, Open
Data Visualization: MS Excel,
Tableau, R and Python
Cloud Analytics: Azure Machine Learning
Database: MYSQL server, MYSQL DB,
1. Data Science course from
2. Done Mobile Making
Workshop held at IIT
3. Participated Networking
Workshop held by IIT
To acquire a Machine learning/Artificial Intelligence position in an association that gives me an open door for self-change and Initiative, while adding to the representative development of the association with my specialized and sensible abilities in the field of Data Science. PROFESSIONAL SUMMARY
Practical exposure in machine learning and deep learning.
Good analytical skills with the ability to collect, analyse, and disseminate significant amounts of information with attention to detail and accuracy.
Proficient in classification algorithms (logistic regression, SVM, kernel SVM, random forest, neural network) using
Expertise in regression models (Linear regression, Multiple linear regression, step methods and application of family of regressions).
Knowledge in clustering models like K-means, Hierarchical.
Using Tableau, prepares quick visualization.
Ability to work independently in quickly involving environment. PROJECTS
1. Classifying the different types of glass
The problem is to forecast the type of class on basis of the chemical analysis. The study of classification of types of glass was motivated by criminological investigation. At the scene of crime the glass left can be used as evidence.
2. Prediction of Flight Delays based on different factors Flight delays are mostly common in all the parts of world due to different factors. It is happens mainly due to heavy traffic in the runway or may be due to bad whether conditions. It is very important to detect the delays in the flights so that decisions can take by the authority whether to land the flight in that Particular Airport.
3. Grouping the different types of customers
There are different groups of people who will go the mart, so now if we want to know the types of customers those who are coming to mart for buying things or not, this can be done by grouping the customers who are coming to mart by this we can get a conclusion whether the customer is loyal or not.
4. Object detection: (Vehicle/Person/Object detection) Object detection is most profound aspect of computer vision due to the number of practical use cases. Object detection refers to the capability of computer and software systems to locate objects in an image/scene and identify each object. Object detection has been widely used for face detection, vehicle detection, pedestrian counting, web images, Security Systems and driver less cars.