rathod-shubham Goto Github PK

followers: 11.0 following: 10.0 repos: 67.0 gists: 0.0

Name: SHUBHAM SHANKAR

Type: User

Bio: 🧟 A Tech Enthusiast, Exploring Possibilities.

Location: Austin, TX

Blog: https://shubham-shankar.netlify.app/

Hello 👋, Shubham Rathod here!

~ You may also know me as Shubham Shankar !

About Me 🦦

I'm a passionate data scientist 😎 exploring possibilities.
Computer Science Grad 🎓.
I have a simple goal: Develop products that improve human lives.
My journey in the world of data began with a curiosity for uncovering hidden patterns and a desire to solve real-world problems.
Check out my repo for some cool content 🤠. Let's explore the data-driven world together! 🚀

, ,

Area of Interest 🐍

#!/usr/bin/python
# -*- coding: utf-8 -*-


class AreasOfInterest:

    def __init__(self):
        self.role = "Machine Learning Engineer"
        self.current_favourite = ["Generative AI", "AWS Cloud"]

    def favourite(self):
        favourite_topic = ['Data Science', 'System Design', 'Algorithms & Data Structure', 'Cloud Computing', 'Software Engineering/Development', 'Full Stack Development']
        
        for fav_top in favourite_topic:
            print(" These are my all time", fav_top)


if __name__ == '__main__':
    obj = AreasOfInterest()
    obj.favourite()

Articles 🗂

Paper 📝

AI-Based Vehicle Damage Detection

Tech Stack

🛠 Language

🗃 Database

🦖 Library

🧨 Framework

🌩 Cloud

Looking for me? 📫

⦿ 🌐 Check out my Portfolio

⦿ 🤝 Connect with me on LinkedIn

⦿ 📩 Shoot Me an Email

⦿ Follow me on Github

⦿ 📝 Read my Articles here

⦿ 💻 Checkout my presentation on Youtube

⦿ 📈🔖 View my certifications

⚡ Fun fact: ... I write poems🎶 ... Do reach out if you find that enchanting😜

~ With love from Shubham Shankar 🖤

SHUBHAM SHANKAR's Projects

500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

amazon-cloud

List of amazing AWS Services that can be utilized.🚀

amazoncomprehend-natural-language-processing--nlp

Amazon Comprehend is a natural-language processing (NLP) service that uses machine learning to uncover information in unstructured data. The service can identify critical elements in data, including references to language, people, and places, and the text files can be categorized by relevant topics.

android

A simple Calculator built using Kotlin

artificial-intelligence

A curated list of my Artificial Intelligence project.

augmentation

Data augmentation is a technique of artificially increasing the training set by creating modified copies of a dataset using existing data. Here is a notebook of different augmentation techniques.

aws

AWS SDK for Python (Boto3) to create, configure, and manage AWS services

aws-bedrock

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) via a single API, along with a broad set of capabilities we need to build generative AI applications with security, privacy, and responsible AI.

basic_python

This repository serves as a template for Python projects, providing a structure and examples to kickstart my development process

blockchain

Blockchain is a decentralized, transparent, and secure digital ledger that records transactions across multiple computers. It uses cryptographic techniques to ensure immutability and integrity.

breakingbadcast

Built this react project based on one of my favorite shows of all time Breaking Bad.

building-data-science-applications-with-fastapi

Building Data Science Applications with FastAPI, Published by Packt

clip-classifier

CLIP is a multi-modal, zero-shot open-source paradigm. Without optimizing for a specific purpose, given a picture and text descriptions, the model can predict the best suitable text description for that image.

cloud_computing-adb

Cloud Computing Project - Web application created and hosted on different cloud platforms.

computer_networks

Wireshark Projects: Wireshark is a basic tool for observing the messages exchanged between executing protocol entities and is called a packet sniffer. My reading from the lab are available here.

covidtracker

Developed a covid tracker that tracks overall cases, recovered cases, and deaths across the globe.

cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

data-science-interview-preperation-resources

Resoruce to help you to prepare for your comming data science interviews

data-science-interview-questions-answers

Curated list of data science interview questions and answers

data-science-interview-resources

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

database-managment-system

In this project, I have designed and implemented a database for keeping track of information about a DBMS subsystem for managing discretionary access control.

datamining-fivetask

Data Mining project : Built a classifier, trained a classifier, created clusters, performed 5-fold-cross-validation.

datascience_textbooks

datastructure-and-algorithm

Computer science is the study of problems, problem-solving, and the solutions that come out of the problem-solving process. This repo contains solutions to algorithmic problems from various platforms like AlgoExpert, LeetCode, HackerRank, CodeSignal, etc.

deeplearning

Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input.

deeplearning.ai

Some work of Andrew Ng's course on Coursera

detectron-2

Detectron2 is an open-source computer vision library by Facebook AI Research. It provides a flexible framework for training and deploying object detection models. Built on PyTorch, it offers modular components, efficient GPU utilization, and supports tasks like instance segmentation and keypoint detection.

diffusionmodel

Diffusion models are deep generative models that work by adding noise (Gaussian noise) to the available training data (also known as the forward diffusion process) and then reversing the process (known as denoising or the reverse diffusion process) to recover the data.