Dipesh Paul

Machine Learning Engineer

Experienced data scientist skilled in building data-intensive applications using predictive modeling, data processing, and Python, able to translate business goals into deliverables.

About Me

I'm Developer- specialized in Machine Learning.

Through my 4.7 years of my career I have real world exposer of projects, client interaction, team management, architecture designing. I am able to provide high quality services.

Skills & abilities

  • Machine Learning
  • Deep Learning
  • Python
  • Tensorflow
  • Transformers
  • Machine Vision
  • Natural Language Processing
  • Git, Jira
  • FastAPI
  • Docker
  • Jenkins


Experience Working

Work Experience

Zdaly, Bangalore, Karnataka

Machine Learning Engineer

Feb 2023 - July 2023

Machine Learning Engineer with expertise in Python, Tensorflow, Scikit-learn, Pandas, Transformers etc.

Great Software Laboratory (GS Lab), Pune, Maharashtra

Data Scientist

Jan 2022 - Jan 2023

Machine Learning Engineer with huge experience in Python, and it's framework like FastAPI, Django, Tensorflow etc.

Calsoft Private Limited, Pune, Maharashtra

Data Scientist

July 2019 - Jan 2022

Innovative and deadline-driven Data Scientist with 3 years of experience in Machine Learning.

Calsoft Private Limited, Pune, Maharashtra

Data Scientist Intern

Jan 2019 - June 2019

Completed 6 Months of internship Machine Learning.


Bachelor of Engineering, Indore, Madhya Pradesh

RGPV University

2015 - 2019 | Computer Science

Acropolis Institute Of Technology And Research - AITR

PCM, M.P. Board

MP Board


Karnataka Vidya Niketan


MP Board


Adarsh Shishu Vihar H. S. School


Title: Product Chat Agent

Technology Used: Python, Langchain, OpenAI, FastAPI, Prompt Engineering

Using Python, Langchain, OpenAI, FastAPI. Created a project that leverages the power of Langchain and OpenAI's Large Language Model to create an intelligent chatbot capable of providing users with detailed product information and facilitating product purchases based on user prompts.

Title: Price Analysis with Scraping

Technology Used: Python, FastAPI, AI/ML, Tensorflow, Jenkins, Docker, Scrapy, Transformers.

Scraped data for pricing strategies for laptops, desktops, and gaming devices and build an ML model for price prediction. Collected data from various E-Commerce and OEM websites across the globe.

Title: Automation of Virtualization

Technology Used: Python, FastAPI, AI/ML, Tensorflow, Jenkins, Docker, Transformers.

Create tool for automate virtualization solution, and providing PAAS service to customer. This tool will be used by customer to create virtual machine, and deploy application on it. This tool will also provide monitoring and troubleshooting service to customer. This tool will also provide AI/ML based price prediction to customer.

Title: Ticket Analyzer

Technology Used: Python, Kafka, Docker, FastAPI, AI/ML, Fastai.

Automate the ticketing tool, with the help of Machine Learning. Where technologies like NLP and Wikipedia trained ULMfit Fastai models are used to fine-tune our Ticket dataset and to find out the ticket and assigned person.

Title: Oil Price Prediction

Skill Used: Python, Kafka, Plotly, Docker, AI/ML with Fastai and Tensorflow

The goal is to analyze the growth of markets like refineries, stock, etc. with the help of user reviews, sentiment, and comments. By using Fastai and Keras with Facebook's Roberta, LSTM, ULMFit, etc. to fine-tune the model.

Title: Avatar Generator

Skill Used: Python, AI/ML, Tensorflow, OpenCV, DZone

Create avatars for human faces for the portfolio. Trained the model using the images dataset of approximately 143,000 images of Humans and Cartoons. Many different architectures of Neural Networks, Deep Convolutional GANs (Style GAN), CNN, UNet to train the model.

Title: Steel Defect Detection

Skill Used: Python, FastAPI, AI/ML, Fastai, and Keras

Detection of steel sheet defects needs to find using Machine Learning, this automation approach leads the industry to high-quality steel production. Build the custom CNN model with U-Net and using Keras. This automation is run as a web app build with FastAPI.


Machine Learning: Stanford University

Grade Achieved: 96.47%

Click Here to view

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Grade Achieved: 99.28%

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Supervised Machine Learning (Regression and Classification): DeepLearning.AI, Stanford University

Grade Achieved: 100%

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Python Data Structures: University of Michigan

Grade Achieved: 98.40%

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I am YouTuber by Hobby...

On the way of spreading knowledge

I love teaching, so I teach on YouTube,
Medium.com, Blogs etc.

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Let's Connect

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Email me at-
[email protected]