Hi everyone!
I am Siddhi and my passion for building machine-learning solutions has made me pick machine-learning engineering as a career. I have been working with machine learning, deep learning, computer vision, and machine learning operations for the last 5 years. Currently, I am just a student with a lot of time to work on my repo. You can check out my projects here.
My first job was as a data scientist in one of the subsidiaries of a prestigious fintech company in Nepal called extensodata. At extensodata, I mostly tangled with huge structured fintech data ranging from banks to e-wallets. I began realizing that data science is a huge field and can get very vague.
I wanted to specialize in computer vision and joined Leapfrog, where I worked on some image segmentation and object tracking projects. After working for a year, I decided to continue my studies and joined the graduate program at the University of South Dakota.
- Languages and Scripts: Python, Bash, C/C++
- Frameworks and Libraries: Pandas, Scikit-learn, Numpy, Seaborn, Plotly, Scipy, Django Rest Framework, Keras(with Tensorflow), TF Lite, Tensorflow TensorRT, Pytorch, Darknet (For YOLO), OpenCV, Tesseract
- IDE: NVim, Jupyter Notebook, Pycharm, VSCode
- Database: MySql, PostgreSQL, MongoDB
- VCS: Git, Github, Bitbucket, Gitlab
- Cloud services: (AWS) S3, EC2, Lambda
- Containerization, and orchestration: Docker, Docker-Compose
- Collaboration: JIRA, Trello, Slack
- Methodology: Scrum, Kanban
- ETL: Pentaho, Airflow, Dragster
- Messaging Broker: RabbitMQ
- Big Data Technology: Apache Spark, HDFS, PySpark (SQL, MLLib)
- Visualization: Microsoft PowerBi, Apache Superset, Python Libraries (Matplotlib, Seaborn, Plotly, Dash)
- ML-Ops: Weights and Biases, MLflow, Tensorflow-Serve
- Hardware: Jetson Nano Developer Kit.
- Operating System: Linux, Windows
Leapfrog Technology
- Lead and mentored the AI/ML team for project delivery.
- Lead end-to-end client requirement elicitation process.
- Defined & developed standard ML practices.
- Used deep-learning frameworks such as darknet, OpenCV, and Tensorflow TRT to train & evaluate YOLO models for object detection.
- Build, Deploy and Maintain statistical, ML, and Deep learning using standard ML\MLOps frameworks such as MLFlow.
- Model tuning and optimization focused especially on deep learning models for embedded devices (NVIDIA Jetson Developer Toolkit).
- Worked on a multi-object tracking project using quantized YOLO tiny models for object detection, & deepsort for tracking.
- Worked on a prototype for a calorie estimator by segmenting the items on a plate using Masked RCNN.
- Experience working with human-computer interaction.
- Worked as team manager for the AI team.
Extensodata Pvt. Ltd
- Use and development of Data Architectures.
- Explanatory Data Analysis (EDA) in SQL as well as Jupyter notebooks.
- Using big data tools such as Hadoop, Spark, Hive, etc to manage huge volumes of data effectively.
- Data visualization using python libraries (seaborn, Matplotlib) and other third-party tools such as PowerBi & Apache Superset.
- Using various machine\deep learning models in spark (MLLib) as well as python (Sci-kit Learn, Keras).
- Using Pentaho and spark for extraction, transformation, and loading data from raw data (files, database, HDFS, hive) to required data architecture.
- Study feasibility, pros, and cons of machine learning and statistical models.
- Query optimization in a relational database (Mysql) for quicker data analysis.
- Writing automation scripts for various purposes (such as ETL, web scraping, etc) using python and Linux shell scripts.
- Studying the application of machine learning models in the banking domain.
- Generating and studying relevant using different feature engineering techniques (such as custom and quartile binnings, combining multiple features) in bank-specific data.
- Building prototype machine learning models on an ad-hoc basis as well as deployable backend data structures.
- Writing stored procedures and scripts to generate various reports from source data for UI consumption.
- Mentoring interns, trainees, and Junior members of the Team
Introduction to Machine Learning in Production
Coursera (July 2022)
https://coursera.org/verify/AQYAFFTRKJW9
Optimize TensorFlow Models For Deployment with TensorRT
Coursera (June 2022)
https://coursera.org/verify/K343P63ZCMNR
Speak Like a Pro: Public Speaking for Professionals
Udemy (June 2022)
UC-9c99a21f-818b-43fa-9f06-34f457356a6d
Deep Learning Computer Vision™ CNN, OpenCV, YOLO, SSD & GANs
Udemy (May 2022)
UC-cea3a356-fa52-46a5-8120-f09bcea73506
Machine learning Deep Learning Model Deployment
Udemy (Oct 2021)
UC-cea3a356-fa52-46a5-8120-f09bcea73506
Applied Artificial Intelligence Club
President
SGA Club, University of South Dakota
University of South Dakota
Masters in Computer Science, AI Specialization (2022 Fall)
Expected Graduation: December 2023
Tribhuvan University
Bachelor in Computer Engineering, KEC (Tribhuvan University) (2014-2018)