IAV GmbH

* Working with Large Language Models (LLMs) to build a custom framework.
* Finetuning of Large Language Models using efficient techniques like PEFT.
* Automatic Prompt Engineering for LLMs.
* Zero-shot, Few-shot Learning, Retrieval Augmented Generation (RAG).
* Software: LangChain, OpenAI, Azure, HuggingFace

Large Language Model Student

ZEISS Microscopy

* Collaborated to library- pylibCZIrw which deals with CZI (Carl Zeiss Image) format for microscopic image data.
* Implemented compression and custom metadata functionality for images in pylibCZIrw.
* Dealing with C/C++ bindings for Python wrapper.
* Code reviews of Pull Requests (PR) on Github repositories on the AzureDevOps environment.
* Wrote unit tests and integration tests and integration in CI/CD pipelines.
*  ApeerML: Contributed to RCNN-based image analysis and instance segmentation, accelerated prediction speed by 5%.
* Deployed and monitored machine learning models on AzureML using Kubernetes.
* Software: Python, Keras, Tensorflow, Numpy, Github, Jupyter, Anaconda, and Pandas, Azure

Machine Learning Student

Quantiphi

*  Insurance Claims Process Automation: Build ResNet (CNN (Convolutional Neural Network) -based) deep learning classification model to categorize documents based on whether they include checkboxes or not followed by detection using OpenCV.
*  Implemented Optical Character Recognition (OCR) for text detection from images and attained a 0.8 fuzzy-wuzzy ratio.
* AWS Textract to perform OCR of PDF documents.
* Software: Python, Keras, Tensorflow, Numpy, Github, Jupyter, Anaconda, AWS, Lambda, SageMaker, S3.

Machine Learning Engineer

Spectral Tech AI

* Data Enhancer: Created question and answering model to exrtract business-related data by finetuning the BERT language model.
* Deployed the model using Flask on AWS EC2 as REST API.
* Working with DialogFlow and deployed using Google Cloud Functions on GCP.
* SkinX: Skin cancer classification using Convolution Neural Network and scored F1 of 0.85.
* Anomaly Prediction: Build an anomaly detection module to predict whether a patient will show up or not using Random Forest, Support Vector Machine (SVM), and Logistic Regression, AdaBoost.
* Worked with AWS (S3, SageMaker, EC2, Lambda) for end-to-end machine learning pipelines.

Data Scientist

Robofied

* Planning and Creating content of Machine Learning for the potential audience. (blog.robofied.com)

* Contributing to an Open-source project Voicenet which comprises of modules which deals with voice data application such as Gender detection, Emotion Understanding from Voice. (https://github.com/Robofied/Voicenet)

* Gender Detection, Emotion Understanding are performed using classical machine learning approaches such as Gaussian Mixture Models, Decision Trees, Bagging algorithm.

* Recognizing text from Captcha using OpenCV and Computer Vision Techniques like deep learning models such as Convolutional Neural Network.

Machine Learning Engineer (Open source)

Anblicks

* Retail Sales Forecasting: Forecasted retail quantity and price using Time Series Analysis.
* Implemented classical forecasting approaches - ARIMA, Holtwinters, Particle filtering, Kalman Filters, and deep learning approaches - LSTM, RNN, TCN (Temporal Convolutional Network).
* Churn Prediction: Performed binary classification to predict churn customers on 1M data points.
* Binary classification is performed using machine learning algorithms with statistical analysis and data processing in Python and Pandas.

Data Scientist Intern

MSME-Technology Development Centre (PPDC) Agra 

Developed in Codeigniter (PHP MVC), this application significantly benefits MSME (Government of India) by automating certificate generation. It features direct CSV import and embeds QR codes on certificates for easy verification, streamlining administrative processes efficiently.

Software Development Internship

Hey! I'm Ridhima, thanks for taking out time and checking my profile.

I am a passionate Machine Learning enthusiast with a strong foundation in Computer Vision, Generative AI, and Large Language Models. My journey in data science has been marked by diverse experiences. I am currently honing my skills in Large Language Model frameworks at IAV GmbH.

My work includes developing state-of-the-art models, training or fine-tuning deep learning models, and deploying scalable machine learning solutions. With a Master's in Data Science significantly enriched my mathematical and research skills, enabling me to develop sophisticated machine learning and deep learning models. With my experience and a rich portfolio of projects, I am keen on applying my expertise to solve complex, real-world problems.

Contacte Me: garg.ridhima72@gmail.com 
Github: https://github.com/ridhimagarg
Website: https://ridhimagarg.github.io/

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