Palak Agarwal

Final Year (B.Tech)

Electronics & CommunicaƟon Engineering

Jaypee InsƟtute of InformaƟon Technology

Noida

EducaƟon

****-****

B.TECH. IN ECE

JIIT, Noida

CGPA : 7.6/10

****-****

AISSCE, CBSE

Kiddy’s Corner Public School

Percentage: 80%

2014-2015

AISSE, CBSE

ST. Paul’s School

CGPA : 9.4/10

Links

Github:// PalakAgarwal

LinkedIn:// palak-agarwal

Skills

Languages

C/C++, Python

Database

MySQL (HackerRank: 5 star)

Latex

Data Structures

Machine Learninng

Hobbies

Sketching

Reading

Swimming

Noida, India

Mobile : +91-934*******

Email : admtb5@r.postjobfree.com

Projects

ForecasƟng Short-Term Solar Irradiance using StaƟsƟcal method JUL-AUG’ 2019

• Time Series data is modeled using Auto Regressive Moving Average (ARIMA).

• The prototype is built in Python using Sklearn, Statsmod- els, Numpy, Matplotlib, Pandas.

Deep Learning Techniques for Short-Term Solar Irradiance forecasƟng SEP-DEC’ 2019

• Solar Irradiance dataset is preprocessed using Principal Component Analysis (PCA).

• A non-linear model is built using Long Short-TermMemory

(LSTM), trained using StochasƟc gradient descent.

• Built model’s weights are opƟmized using Bio-inspired al- gorithms (Cuckoo Search and Grey Wolf Algorithms). COVID-19 Effect: PredicƟng Stock Market indices based on analysis of Public senƟment and discussions on TwiƩer during the Pandemic MAR-JUL’ 2020

• Text data is scraped fromTwiƩer’sAPIusingTweepylibrary in python.

• Opinion mining is performed using techniques like SenƟ- ment Analysis and Topic Modelling.

• Stock market indices are predicted using models like linear regression and Long Short-Term Memory (LSTM).

Experience

INTERNSHALA Machine Learning Trainee

• Working with Python libraries JUN-JUL’ 2020

• Data manipulaƟon and exploraƟon

• PredicƟve Modelling

• Supervised and unsupervised learning

Naaniz Seller Services Pvt. Ltd. Machine Learning Intern Kitchen surveillance system JUN-AUG’ 2020

• Data is scraped using FastAI from google images.

• Dataset is labelled using Labellmg.

• Object detecƟon and classificaƟon model is built using YOLOv4 on customdatasettoensurehygieneandsafetymeasuresbeing taken during COVID-19 pandemic.

Achievements

• Runner-up at CONVERGE 2018.

Annual sports fesƟval of Jaypee InsƟtute of InformaƟon Technology in Basketball.

Contact this candidate