Nehal Gupta

I'm currently in my 3rd year in my B.Tech. I have been studying Machine Learning for about 3 months now through online sources as well as offline training. I have experience working with the following libraries - Numpy, Pandas, OpenCV, SMTP, sklearn (linear regression, knn, neural networks etc), Keras, paho-mqtt, Tenserflow etc. I have also developed algos for Face swaping, multiple object detection, CNN. I think I should be hired for this internship because being a young individual, I'm creative and posses new ideas. I am hard working and have the dedication towards work.Being a fresher, this will be a great opportunity to explore my knowledge in an area I'm really interested in.
Some of the below mentioned projects use live video capture algorithms in order to process real-time information. I've done the following projects in Computer Vision and Machine Learning which show my experience so far-
Links to all the projects-

1. https://drive.google.com/open?id=1lFGjcyU4RnOSlzFLm0RV_JhOzx6fjO29
   2)https://drive.google.com/open?id=1zIF69isgy3kU0O-scXeGHpZLsXGd_SlX
   3)https://drive.google.com/open?id=1dNYnWpCQD2YUSNbMK_e-KPyHmib9nolW
   4)https://drive.google.com/open?id=16VemrqloHPStQGOdokbadxET9QYYTsCW

1)Facial Bio metric Attendance- A facial biometric attendance system using openCV, smtplib, pandas and face_recognition library having following features-
->Using a webcam detects the face of a student and checks if it's present in the database by comparing it with already present encodings. If it's not present then it'll add his/her name and email id and adds to database.
->Calculates total attendance and sends a mail of the total attendance till present date on the student's email id. (using smtp library)

2)Music player using facial expression - Detects the face of the user and detects the expression using miniXception model to detect expressions. According to the expression detected plays, shuffles music according to user input.

3. Jarvis - A basic idea of a chatbot that uses-
   -> Admin configuration
   -> weather, wikipedi and other API's
   -> Speech to text and text to speech conversion using pyttsx3 and speech_recognition
   -> performs google search and other basic features.

4)Insurance policy loss amount predictor - I used the dataset of medical insurance and predicted the loss amount granted. The features determining the amount were- Age,Sex, No. of children ad well as the region they live in. It also consists of a plot that shows the comparison between the actual loss amount and the predicted loss amount for 1 sample of 100 training sets.