Priyanshu Yashwant Deshmukh

AG2.ai

Full Stack Engineer

June 12, 2026 – Present

ag2

November 11, 2024 – Present

AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at: https://discord.gg/sNGSwQME3x

Text-Guided-Sketch-to-photo-Image-Synthesis

August 13, 2023 – August 21, 2023

a text-guided sketch-to-image synthesis model that semantically mixes style and content features from the latent space of an inverted Generative Adversarial Network (GAN). Our goal is to synthesize plausible images from human facial sketches and their respective text descriptions.

sEmantic_sentence_similarity_model_api_with_transformers_and_tensorflow

July 9, 2023 – September 29, 2023

an api for the sns model created (semantic sentence similarity model using tansformers ,tenosrflow and fastapi ) : hosted on aws

Ice-Sejj

May 2, 2023 – May 7, 2025

Introducing Ice-Sejj: Your Ultimate NLP and Machine Learning Solution

ecommerce-website-customer-churn-data-analysis

March 26, 2023 – March 26, 2023

given an ecommerce website I have to perform data analysis on customer churn and extract insights from it

BBC-News-Classification-using-hugging-face

March 9, 2023 – March 9, 2023

classify news into five categories: business, entertainment, politics, sport, and tech.

Abstractive-Text-Summarization-Enhancing-Sequence-to-Sequence-Models-Using-Word-Sense-Disambiguatio

February 2, 2023 – September 29, 2023

This repository contains code and resources for abstractive text summarization (TS) using a novel framework that leverages knowledge-based word sense disambiguation (WSD) and semantic content generalization to enhance the performance of sequence-to-sequence (seq2seq) neural-based TS.

Uniacco-assignment-cust-churn-prediction-model

January 30, 2023 – January 30, 2023

Uniacco-assignment-cust-churn-prediction-model — GitHub repository

classification-mobile-price-analysis-

October 19, 2022 – October 19, 2022

Create a classification model to predict whether price range of mobile based on certain specifications

coffee-machine-project

August 28, 2021 – August 28, 2021

1. Prompt user by asking “ What would you like? (espresso/latte/cappuccino): ” a. Check the user’s input to decide what to do next. b. The prompt should show every time action has completed, e.g. once the drink is dispensed. The prompt should show again to serve the next customer. 2. Turn off the Coffee Machine by entering “ off ” to the prompt. a. For maintainers of the coffee machine, they can use “off” as the secret word to turn off the machine. Your code should end execution when this happens. 3. Print report. a. When the user enters “report” to the prompt, a report should be generated that shows the current resource values. e.g. Water: 100ml Milk: 50ml Coffee: 76g Money: $2.5 4. Check resources sufficient? a. When the user chooses a drink, the program should check if there are enough resources to make that drink. b. E.g. if Latte requires 200ml water but there is only 100ml left in the machine. It should not continue to make the drink but print: “ Sorry there is not enough water.