Machine Learning Computer Science

Kaushik Mukherjee Github: kaushikmastro

LinkedIn: linkedin.com/in/kaushik

SUMMARY

• Enrolled as a master student at Freie University Berlin.

• Trained Physicist with scientific approach to problems solving; Self-enabled Computer Scientists with mind- set to add value to the ecosystem. Interested in data heavy AI/ML roles of Data Analyst, Data Scientist and Machine Learning roles.

• Python, Large dataset handling, Data Analysis, Statistics, Data Modelling, Dataset Training, ML modelling, Deep Neural Network Architecture, Databases, SQL, ETL, MS Excel, Github, Ubuntu. PERSONAL INFORMATION

E-mail: **********@*****.***

Phone No: +491*********

Address: Gallierweg 25, 53117 Bonn, Germany.

EXPERIENCE

University of Bonn Bonn, Germany

IT Student Assistant September 2021- April 2022

• Responsibility of maintaining the crctr224 website which involved data entry and debugging html codes.

• Maintaining and analysing data on Excel sheets, formatting Word and pdf documents and fixing hardware troubleshooting.

University of Bonn Bonn, Germany

Student Research Assistant September 2021- November 2021

• Worked as an image annotator for the Photogrammertry institute for training neural networks to detect crops amongst weeds.

• Developed expertise on data annotator tools and editing source code. Argelander-Institut f urAstronomie Bonn, Germany

Research Intern November 2020- December 2020

• Became a part of the sub mm astronomy group and contributed to project involving simulation of higher order SZ signals.

• Wrote Python scripts for simulating temperature maps, white noise maps and created radial profiles. Argelander-Institut f urAstronomie Bonn, Germany

Master Thesis Februrary 2021- April 2023

• As a part of the sub mm astronomy group contributed to forecasting of cosmological signals for upcoming telescopes.

• Wrote Python scripts for simulating different cosmological signal maps, wrote codes for sophisticated noise reduction algorithms like ILC and cILC, wrote codes for MCMC simulations for map stacking, signal pro- cessing, analysed image data and implemented polynomial fitting on them. COMPUTATIONAL SKILLS

• Programming - Python (Proficient), C (Basic), FORTRAN (Basic), SQL.

• Data Engineering - SQL, IBM Db2, Data ETL, SQLite3

• Machine Learning libraries - Scikit-learn, TensorFlow, Keras, NumPy.

• Data Visualization tools - Matplotlib, Seaborn, Google Charts.

• Operating Systems - Linux, Windows.

• Office - Microsoft Word, Excel, LibreOffice Writer.

• Others - Jupyter Notebook, SPSS, IBM Db2, Latex, HTML, Github.. EDUCATION

University of Bonn

Masters in Astrophysics October 2019 - April 2022

• Thesis: Detectability of the higher order Sunyaev-Zeldovich effect with future experiments.

• Skills: Python, Data Analysis, Machine Learning, Statistics, Latex, Linux. Amity University Kolkata

Masters in Applied Physics August 2015 - May 2017

• Thesis: Maximal temperature in a thermodynamical system.

• Skills: FORTRAN, Mathematica, analytical and complex problem solving, Lab expertise. University of Calcutta

Bachelors in Science Physics July 2010 - May 2015

• Studied Physics, Mathematics and Computer Science.

• Skills: C, analytical and problem solving.

INTERNSHIPS AND CERTIFICATIONS

Advanced Machine Learning from Coursera

• Learnt in depth concepts of supervised unsupervised ML, linear logistic regression, cost functions, gradient descent, regularization, neuron networks, tensorflow models, decision trees. Wrote Python scripts using scikit-learn, tensorflow to implement these in solving real-life problems. Spliting datasets into train, cross validation and test.

• Solved numerous coding exercises. Built neural network in Tensorflow, compared several neural architec- ture, contributed to time series forecasting modelling to predict weather, built a neural network model for predicting hand written digits.

Advanced SQL from Coursera.

• Familiarity with relational databases, data modelling, running queries on datasets, filtering, grouping datasets, joining different data tables using inner and outer joins, concatenating string.

• Solved numerous queries on several company datasets to deduce employment history, delayed pensions of employees, profitable expansion, etc.

Data Science Training at Brainnest.

• Intense learning of statistical concepts of distribution, probability hypothesis testing, Box-Cox transforma- tions, Pearson correlation, Shapiro Wilk test, t-tests, ANOVA and implementing them on datasets using the SPSS tool.

• Analysed several datasets including titanic, cholesterol data, sales data, etc in order to derive correlation between data sets, visualize them and conclude statistical significance. IBM Data Engineering from Coursera.

• Concepts about SQL and noSQL, ETL processes, Big Data, Data Pipeline, web scraping. Implemented SQL queries on IBM Db2 platform on comapny datasets to deduce results.

• Contributed to projects by writing Python scripts to create databases and loading volumes of data using sqlite3, extracting data from different file formats and transforming data, scrap data from websites to perform queries on them.

LANGUAGE SKILLS

• English (bilingual/native).

• Bengali (mother tongue).

• Hindi (native).

• Deutsche (beginner).

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