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šŸ‘‹ Hi there, I'm Bhargob!

Machine Learning Researcher | Technical Writer @Medium | AI Consultant

šŸŒŸ Bio

I am a Machine Learning Researcher with over 5 years of experience and a PhD in applied ML. A technical writer @ Medium (Level Up Coding) and an AI consultant.

  • šŸ”­ Iā€™m currently working on building my profile as an AI/ML educator. Preparing for my first series on Youtube. Do watch out!
  • šŸŒ± Iā€™m currently learning how to become a content creator in the Generative AI space.
  • šŸ‘Æ Iā€™m looking to collaborate with startups and buisnesses either as a technical writer or as a consultant/advisor.

šŸ§° Tech Stack

Python

PyTorch

C++

HTML

CSS

Hugging Face

Docker

MATLAB

AWS Cloud

Google Cloud

GitHub



Socials

gmail medium linkedin




Email: [email protected]


Bhargob Deka's Projects

agvi-python icon agvi-python

This is the python package for approximate Gaussian variance inference: an analytical method for quantifying uncertainty in time series modeling

agvi-v1 icon agvi-v1

The package provides a new method for the online inference of error variance parameter for both univariate and multivariate errors.

ats-resume-analyzer icon ats-resume-analyzer

This is an ATS Resume Analyzer using the Gemini Pro model through Vertex AI and the magic of prompt engineering.

computer-vision icon computer-vision

In this repository I will provide codes for performing various computer vision tasks such as classification, object detection and image segmentation.

cutagi icon cutagi

CUDA implementation of Tractable Approximate Gaussian Inference

deep-ensemble icon deep-ensemble

This repository shows the application of the deep ensembles method in case of multi-output regression tasks. The original code is from the PyTorch implementation by Lakshminarayanan et al. (2016) -> https://arxiv.org/abs/1612.01474

deep-ensembles icon deep-ensembles

PyTorch implementation of Lakshminarayanan et. al (2016) https://arxiv.org/abs/1612.01474

dun icon dun

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

generate-images-houseplants icon generate-images-houseplants

This repository focuses on generating images of healthy and non-healthy houseplants using some real data with the help of Generative Adversarial Networks

hands-on-llms icon hands-on-llms

šŸ¦– š—Ÿš—²š—®š—暝—» about š—Ÿš—Ÿš— š˜€, š—Ÿš—Ÿš— š—¢š—½š˜€, and š˜ƒš—²š—°š˜š—¼š—æ š——š—•š˜€ for free by designing, training, and deploying a real-time financial advisor LLM system ~ š˜“š˜°š˜¶š˜³š˜¤š˜¦ š˜¤š˜°š˜„š˜¦ + š˜·š˜Ŗš˜„š˜¦š˜° & š˜³š˜¦š˜¢š˜„š˜Ŗš˜Æš˜Ø š˜®š˜¢š˜µš˜¦š˜³š˜Ŗš˜¢š˜­š˜“

houseplant-healthy icon houseplant-healthy

This is an end-to-end project for classifying whether an image of a houseplant is healthy or not (wilted)

laplace icon laplace

Laplace approximations for Deep Learning.

llm-agents icon llm-agents

This project delves into LLM-powered agents created using LangChain and LangGraph. It will contain notebooks used for my blog writing.

multi-agent-apps icon multi-agent-apps

This repository will contain projects on multi-agent applications using frameworks such as crewai, langchain, gradio, hugging face etc.

noise-inference icon noise-inference

A Package for online estimation of noise covariance matrix in state-space models and neural networks.

openbdlm icon openbdlm

Bayesian Dynamic Linear Models for time-series analysis

practical-sql-2 icon practical-sql-2

Code and Data for the Second Edition of "Practical SQL" by Anthony DeBarros, published by No Starch Press (2022).

rag-chat-models icon rag-chat-models

In this repository, I will provide different ways of building RAG chat models using the Langgchain framework.

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