This document contains information about Sahil Malhotra including his personal details, education, skills, work samples, certifications, and work experience. Sahil is currently a final year B.Tech student in computer science who has skills in Python, machine learning algorithms, data analytics and deep learning. He has internship experience in data science, natural language processing, and analyzing tweet sentiment to predict stock market impacts.

1. A B O U T M E
P E R S O N A L
Name Sahil Malhotra
Languages English, Hindi
Mobile +91 9711946194
Email thesahilmalhotra@gmail.com
E D U C A T I O N
College The NorthCap University
Duration 2015-2019
Degree B.Tech in Computer Science
S K I L L S
Python
Data Analytics
Machine Learning Algorithms
Data Structures & Algorithms
C++
Deep Learning (RNN/LSTM)
SQL + Big Data (Spark)
MongoDB
Web Frameworks(Django)Probability & Statistics
I’m in my final year pursuing B.tech in
computer science. I share a great love for
technology, and have been blogging stuff
related to programming. I desire to be a
Data Scientist solving real world problems
and broadening my algorithmic and
machine learning related skillset as much
as possible.
W O R K S A M P L E S
Professional Blog:
https://medium.com/codestudiox
Personal Portfolio:
https://sahil-malhotra.github.io
Github Handle:
https://www.github.com/sahil-malhotra
S A H I L M A L H O T R A
h t t p s : / / s a h i l - m a l h o t r a . g i t h u b . i o
C A L L M E
+91 9711946194
T I M E L I N E
Quora
www.quora.com/sahil-malhotra-32
Linkedin
www.linkedin.com/in/sahil-malhotra
June 17 travel d’globe - Data Science Internship
Content Analysis Tool
Helped in increasing the pagerank of blogs of traveldglobe.com on search engines. This
tool automated content platform of travel d’globe. Created five API Endpoints: Most
searched words, Missing keywords in content, Content Keyword Extraction, Google Rank
Analysis, Plagiarism Detection.
CGPA 7.19/10
C E R T I F I C A T I O N S
Andrew Ng’s DeepLearning and Neural
Network Course: verify at bit.ly/2v0mRlo
Andrew Ng’s Hyper Parameter Tuning and
Optimization course: verify at
https://bit.ly/2RAFF7q
University of Michigan’s Applied Machine
Learning Course: verify at bit.ly/2HH0ZyO
University of Michigan’s Applied Text
Mining Course: verify at bit.ly/2HJFhKU
July 18 Deep Metric Learning
Real Time Face Recognition
The face recognition implementation is both accurate and capable of being executed in
real-time with or without a GPU. Deep metric learning is performed by outputting a real
valued feature vector of an image to quantify the face.
Apr 18 NLP Task (https://git.io/vpLy1)
Spam Message Detection
First tried transforming the data using CountVectorizer and fitted a Multinomial Naive
Bayes’ Model, it didn’t keep account of rare words’ importance.
Secondly, transformed data using Tf-idf Vectorizer and added two more features:
“Length of Doc” and “No. of digits per Doc” and fitted a Logistic Regression Model which
worked well on test set.
Machine Learning (https://git.io/vxYHv)
Blight Ticket Compliance - Predict whether a blight ticket will be paid on time
Enforcing unpaid blight fines is a costly and tedious process. The predictive modeling helps
to predict whether a given blight ticket will be paid on time and thereby save money by
only enforcing those where the chance of a ticket not being paid is high.
Dec 17 Hypothesis Testing (https://git.io/vptcy)
University towns have their mean housing prices less affected by recessions
Steps for Hypothesis testing:
- create new data showing the decline or growth of housing prices between the recession
start and the recession bottom.
- run a t-test comparing the university town values to the non-university towns values.
- checking if the hypothesis is accepted or not by the value of confidence.
Mar 18
Jan 19 Fidelity International - Technology Intern
Tweet Analysis for Sentiment Impact on Stock Market
Analyzing sentiment scores from tweets related to relevant stocks and predicting the
sentiment impact on the market for the next day. Used state-of-art RNNs to evaluate scores.