Manjit Ullal.

Data Scientist | Machine Learning Engineer | Researcher.

About me

Tycho Brahe in the 15th century carefully measured the position of planets. Even though his geocentric model of the world was not correct the act of collecting the data through careful observation emphasized the importance of data in Science. Johannes Kepler looked at the Brahe's measurements and saw a pattern. He modelled that the orbit of the planets around the Sun is not in perfect circles but an ellipse. This was a revelation in Physics. Fast forward, we are living in 21st century, where we have abundance of data. All we need is a careful eye for detail and creative imagination to find the patterns in the data.

I am passionate about Data Science, Machine Learning and Artificial Intelligence. I believe every field and every person can leverage AI for their benefit. Not all problems can be solved using AI. AI certainly will unlock new ways of thinking about the problem and arriving at the solution. Feel free to message me on LinkedIn if you have a position or want to understand my work. I am continually updating my skill set and therefore I can bring something new to the table every time, be it professionally or personally.

Skills

Languages

Python, R, JavaScript

Machine Learning

Supervised Learning:

Linear regression, Logistic regression, Ridge regression, Elastic Net, SVM, KNN, Naive Bayes, Random Forest, Ensemble Methods, XgBoost

Unsupervised Learning:

Gaussian mixture models, Clustering, Kmeans, PCA, SVD, Expectation Maximization

Deep Learning

Computer Vision:

CNN, YOLO, Resnet

Natural Language:

RNN, LSTM, GRU, BERT, Naive Bayes

Framework and Libraries

Pytorch, Tensorflow & Keras.

Flask

Technologies

Git, Docker, Kubernetes

Cloud

AWS, EC2, SageMaker, Lambda

Tools

Tableau

Database

MySql, Postgre, Mongodb, Oracle

Projects

Classic Machine Learning

Title: Implementation of Machine Learning Algorithms by scratch.

Description: Learning key models using first principle, implementing directly from python.

Impact: Understood the implicit data assumptions , Strengths and limitations of the model, thereby learning when to use what model.

code

Title: Exploratory Analysis.

Description: Introductory Analysis to a given dataset

Impact: Learnt different visualization methods to aid analysis.

code

Title: Competition submissions

Description: Solve Data Science challenges and other code challenges

Impact: Experienced different Data Science challenges given by the firms for their position.

code

Neural Networks

Title: Implementation of Transformer Algorithm

Description: Developed the original attention model from the paper "Attention is all you need" using Pytorch. Trained the model on Numeric data for sequence prediction.

Impact:

code

Title: Image Classification

Description: Created a model to detect class of the image. Explored techniques to find the bounding boxes to locate the object within the image.

Impact: Ability to follow computer vision algorithms and model them.

code

Title: Spark

Description: Used Spark , Scala on Twitter dataset and ran mapreduce operation to uncover the count of followers.

Impact: Ability to run machine learning on a distributed system.

code

Blog

https://thecuriouspeopleblog.wordpress.com/

This is a blog dedicated to the inner writer in me. Sharing knowledge and experimenting on Ideas

Contact

email me at ullal.m@northeastern.edu

find me on LinkedIn https://www.linkedin.com/in/manjit-ullal/