Resume based on Machine learning and deep learning

1. ASHUTOSH VISHNOI
B.Tech(Third Year)
Electronics and Communication Engineering
Indian Institute of Information Technology, Design and Manufacturing,
Jabalpur
(An institute of national importance established by Govt. of India)
MOBILE:+917985521330
E-MAIL:
ashutosh.vishnoi.790@gmail.com
LinkedIn Profile:
https://www.linkedin.com/in/ashutosh-
vishnoi-23a0299a/
Kaggle:
https://www.kaggle.com/ashuvishnoi
CAREER OBJECTIVE:
I am seeking for an internship with a challenging, responsible and diverse work environment that would
extract the best of my skills and abilities from me, subsequently resulting in technological and overall growth
of myself and the company.
ACADEMIC QUALIFICATION:
Course Institute/School Year of passing Performance
B.Tech PDPM IIITDM JABALPUR Still Pursuing CPI - 6.5/10.0
12th PSVM INTER COLLEGE KANPUR 2015 Percentage - 89.4%
10th PSVM INTER COLLEGE KANPUR 2013 Percentage - 89 %
SKILLS : Other skills:
1)- Deep learning 1)- C Programming
2)- Machine learning 2)- Arduino/IOT
3)- Python Programming 3)- ISIS Proteus
4)- Computer Vision 4)- Data structure
5)- Matlab/Octave
COURSERA MOOC CERTIFICATES:
1)-Machine learning (Stanford University)
2)-Introduction to data science in python (University of Michigan)
3)-Neural Networks and deep learning (deep learning.ai)
4)-Convolutional Neural Networks (deep learning.ai)
5)- Sequence Models (deep learning.ai )
6)-Applied Machine learning in python (University of Michigan)

2. Projects done:
MACHINE LEARNING AND DEEP LEARNING BASED PROJECTS:
Libraries Used:
1)-Numpy 2)- Pandas 3)-Matplotlib 4)-OpenCv 5)-Scikit learn 6)-Tensorflow 7)-Keras
1)-Predicting House prices:- It is a regression problem to estimate the price of houses . First I
preprocessed the data like removing of null values and normalizing the features. I have used ridge
regression to build the model.
2)-Kaggle Titanic classification problem:- It is a binary classification determining survivors of titanic
tragedy. Dropping out irrelevant features , adding new features and filling up the missing values is the
part of data preprocessing. I have used KNeighborsClassification to build the model with scikit learn.
3)-Image Classification using CNN model:- Model to classify the images of cats among lots of 28*28
pixels pictures using 4-layers neural network after resizing and normalizing the pixel values of the
image.
4)-Digit Recognizer:- I have used keras library to build the convolutional model to recognize the digits
from 0 to 9.
Other projects:
5)-Follow me robot using IOT:- We have implemented a robot that follows a human having follow me
app by detecting gps co-ordinates. We used gps module, arduino, blutooth module, compass and a app
to complete our desired work.
6)-Home automation using IOT:- We have implemented a home automation system using IOT devices
like GSM module and Arduino. In this project anyone can control the home network staying at any place
in the world sending just a command using SMS through cell phone.
ACHIEVEMENTS:
1)- Silver level(4- stars) in problem solving at HACKERRANK in python language.
2)- Hackerearth HDFC bank ML hiring challenge: Built a banking behavioural scorecard for self-employed
customers using supervised learning model. I have used svm model to predict the binary flags with 90%
accuracy and secured 51th rank amoung 1000 participants.
POSITION OF RESPONSIBILITIES:
1)-Workshop Coordinator of Quadcopter workshop in Techfest of IIITDMJ.
2)-Active Member of Electronics club IIITDMJ