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Sahil Kakkar

Machine Learning Engineer

New York, NY, USA
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I am an enthusiastic and results-oriented AI enthusiast currently enrolled in a Master's program in Artificial Intelligence at Yeshiva University.

My journey into the realm of AI commenced with intensive coursework, including completion of a Machine Learning course from Stanford University, the Deep Learning Specialization from DeepLearning.ai, and an Advanced Certificate Programme in Data Science from IIIT Bangalore. These educational endeavors have furnished me with a robust theoretical foundation and practical expertise in Python, PyTorch, fast.ai, scikit-learn, statsmodels, NumPy, Pandas, SQL, Matplotlib, and Seaborn.

My hands-on experience has been enriched through various projects and internships. Notably, one of my projects achieved acclaim, securing the 3rd prize at my college. Furthermore, I had the privilege of interning at IIIT Hyderabad, engaging in cutting-edge AI research.

I am eager to connect and explore potential collaborations on exciting AI projects or delve into discussions regarding the latest advancements in artificial intelligence and machine learning. 

Careers

Research Intern

iHub Data

Internship05/2022 - 06/2022
  1. Worked on "Retinal Developmental Disorder Detection"
  2. Implemented the state of the art research paper
  3. Accuracies achieved on OCTID Dataset were 0.99 (AP) and 0.97 (AUC)
Data Science Fellow

Fellowship.ai

Internship01/2022 - 03/2022
  1. Taught KNN, K-Means, PCA, GBM in the Fellowship.ai's ML course
  2. Synthesised a dataset and implemented a Multi-label classifier
  3. The final accuracy on the validation set was 99%

Education

Yeshiva University

Artificial Intelligence

09/2022 - 09/2024Master's DegreeClass of 2024
Maharaja Agrasen Institute of Technology

Computer Science and Engineering

08/2018 - 08/2022Bachelor's DegreeClass of 2022

My projects

Impostor Detection using Behavioural Biometrics

No image available

- Identified users from their mouse movements by employing intense feature engineering with sophisticated anomaly detection - Trained a unimodal parametric model using Weibull distribution based on a research paper

Role: Feature Engineering and Model Training

Completed: 2/2022

Live project: https://github.com/Sahil1776/Impostor-Detection-using-Behavioural-Biometrics

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Skills
PythonSupervised LearningUnsupervised LearningComputer VisionML algorithmsSQLData cleaningData VisualizationPyTorchScikit-learn
Experience1-3 years
Hourly rate$100/hr
Open to
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