Hi all, I'm Vivek πŸ‘‹

A driven Machine Learning Engineer πŸš€πŸ’‘, proficient in crafting intelligent systems πŸ§ πŸ€– using Python / TensorFlow / PyTorch / Keras, along with various other cutting-edge libraries and frameworks πŸ“˜πŸ’» 🎯.

What I do

MACHINE LEARNING ENTHUSIAST EAGER TO PUSH THE BOUNDARIES OF AI

  • git

  • linux

  • python

  • sql-database

  • mongodb

  • aws

  • docker

  • machine-learning

  • neural-network

⚑ Design and implement machine learning models for predictive analysis

⚑ Develop robust data processing pipelines and optimize AI algorithms for efficiency

⚑ Integration of machine learning models with cloud services like AWS

⚑ Create immersive data visualizations and interpret complex data sets to provide actionable insights

Education

Rutgers University–New Brunswick
Rutgers University–New Brunswick
Master of Science in Data Science

September 2022 - Present

Relevant Coursework:

  • Natural language processing
  • Data Mining
  • Database Management System
  • Data Wrangling
Indian Institute of Technology Madras
Indian Institute of Technology Madras
Bachelor of Technology

July 2018 - July 2022

Relevant Coursework:

  • Introduction to Scientific Computing
  • Introduction to Data Analytics
  • Mathematical Foundations of Data Science
  • Parallel Scientific Computing

Experiences

IQB RCSB, Rutgers University
IQB RCSB, Rutgers University
Senior Python Developer
June 2023 – Current

  • Risk Mitigation Solutions: Developed and implemented machine learning-based risk mitigation solutions, including abusive account detection and fraud detection, resulting in a significant reduction in incidents and improved platform safety.
  • Robust Modeling Infrastructure: Enhanced modeling infrastructure by improving labels, features, and algorithms, leading to increased robustness, automation, and generalization. This reduced the modeling and operational load on risk adversaries and new product/risk ramping-ups.
  • Privacy and Compliance: Contributed to improving risk machine learning excellence by incorporating privacy and compliance considerations, ensuring interpretability, risk perception, and analysis in the models and solutions developed.
Emids
Emids
Machine Learning Engineer
June 2021 – June 2022

  • Advanced Machine Learning Techniques: Utilized advanced machine learning techniques such as deep neural networks, transfer learning, and time series analysis to develop models and algorithms for risk prediction and mitigation, resulting in improved accuracy and effectiveness.
  • Data Processing Efficiency: Optimized data processing pipelines by leveraging technologies like Hadoop, Hive, and Spark, enhancing the efficiency of data cleaning, preprocessing, and feature engineering, leading to faster model development and deployment.
  • Model Interpretability: Implemented model interpretation techniques to improve the explainability of risk models, enabling a better understanding of model decisions and facilitating risk analysis and mitigation strategies.
WorkFence Technologies
WorkFence Technologies
Data Analyst
May 2019 – May 2021

  • Attrition Risk Analysis: Conducted analysis on employee attrition risks using statistical and machine learning techniques, providing valuable insights into potential attrition factors and contributing to the development of targeted retention strategies.
  • Data Visualization: Created insightful visualizations using tools like Tableau to communicate attrition trends and patterns to stakeholders, enabling data-driven decision-making and proactive talent management strategies.
  • Strategic HR Initiatives: Collaborated with HR teams to propose and implement strategic initiatives based on data-driven insights, including improvements in benefit policies, safety measures, and inclusion programs, resulting in a positive impact on employee engagement and reduced attrition rates.

Self-driven Projects

Advanced-NLP-with-Transformers

πŸ”¬πŸ€– Explore advanced NLP with Transformers! πŸ’‘ A hands-on project covering 5️⃣ major tasks: text summarization πŸ“, classification 🏷️, question answering ❓, named entity recognition πŸ“‡, and relationship extraction πŸ’Ό. Leverages Hugging Face's Transformers, PyTorch, SpaCy, NLTK, and more! πŸš€πŸ› οΈπŸ”₯ Happy learning! πŸŽ“πŸ’»πŸŒ

Jupyter Notebook

162.9 MB

Stable-Diffusion-FineTuning

πŸ”¬πŸŽ¨ Dive into the world of text-to-image generation with Stable-Diffusion-FineTuning! πŸš€ From intricate impressionist art πŸ–ΌοΈ to dynamic action scenes πŸš—, this project turns any text prompt into vibrant visuals! πŸ’‘ Perfect your model with fine-tuning, enabling a wide variety of creative applications. 🌟

Jupyter Notebook

25.3 MB

DGL-Fraud-Detection

πŸš€ Detecting financial fraud πŸ’³πŸ’° using Graph Neural Networks (GNNs) πŸ”€! Dive into how GNNs, Amazon SageMaker πŸ§ͺ, and the Deep Graph Library (DGL) collaborate to spot fraudulent transactions from complex datasets πŸ‘₯. Leverage R-GCN models 🌐 for multi-relational data 🎯 and enjoy better predictive performance πŸ†. Experiment with us! πŸ’‘πŸ‘

Jupyter Notebook

31.8 MB

DL-Approach-to-Lip-Reading

πŸ“šπŸ—£οΈ "LipNet: Lip Reading Project" πŸ‘€ Transforms video frames 🎞️ into text πŸ“„ using a spatiotemporal model 🧠🌐 Achieves 95.2% accuracy πŸ† on the GRID corpus, outperforming humans and previous models! Model training, data prep πŸ”„πŸ“‚, and inference πŸ’‘ all included. Code can be run on StudioLab, nbviewer, and Google Colab πŸ”„πŸ’».

Jupyter Notebook

768 KB

Customer-Churn-Prediction

πŸ“ˆ Harness the power of LightGBM, CatBoost, TabTransformer & AutoGluon-Tabular in Amazon SageMaker πŸš€ for customer churn prediction. πŸ’‘πŸ±πŸ”„πŸ“Š We employ Automatic Model Tuning (AMT) to train ML models 🧠, identifying unhappy customers 😞 early to prevent business loss. πŸ’Έ Comparison of models included! πŸ“

Jupyter Notebook

52.2 MB

Twitter-Search-Application

πŸš€ Dive into the 🌊 of tweets with the 🐦 Twitter Search App! Utilizing MySQL & MongoDB πŸ› οΈ, our app fetches, stores, and πŸ” searches through tweets, retweets, and more. Offers an easy-to-use interface, 🎯 several search options, and LRU cache for speedy data retrieval. 🏎️ Keep your Twitter data at your fingertips! πŸ‘ŒπŸ’Ό

Python

146.6 MB

Reach Out to me!

Discuss a project or just want to say hi? My Inbox is open for all.

"Machine Learning Engineer πŸš€πŸ’‘ | Python, TensorFlow, PyTorch, Keras | Always Learning πŸ“˜πŸ’» | Exploring the AI frontier πŸ€–"

New Brunswick, NJ
Open for opportunities: Yes
VIVEK REDDY CHITHARI