Hello I'm

Aditya Mishra

Machine Learning Engineer

About Me

Hello, I’m Aditya, machine learning engineer based on Mumbai. I have experience in developing end to end machine learning project, software engineering, web site design and linux. Also I am good at

  • Hadoop
  • Databases
  • Git
  • Linux
  • Heroku
  • AWS
  • React JS
  • Django
Download Resume

What I do

Machine Learning

Deep Learning

Web Development


Bachelor of Engineering, Computer Science

Mumbai University


Graduated with 8.8 CGPA (A Grade)

Oracle Certified Professional Java Programmer



Java SE 6 Programmer
Passed with 92%

Work Experience

Machine Learning Engineer


June 2018 - Present

Machine Learning Intern

GreyAtom School of Data Science

Oct 2018 - Jan 2019

GreyAtom is a edutech startup that provides Data Science Master Programs. As a ML intern, I helped develop Data Science and ML course materials. Worked with software development teams to ensure accurate integration of machine learning models into firms platform.

Machine Learning Intern

Accelo Innovations Pvt Ltd

Oct 2017

Accelo is a Mumbai based startup. Their product MaMa Drive (Module for Accident Management and Assistance) is a small device that fits on the dashboard and pre-detects accidents and provides immediate assistance to the driver. Worked on Object Detection algorithms to detect objects in real-time. Researched & developed solutions to approximate distace object's distance from cameras.


Boost your Image Classification Model

Image classification is assumed to be a nearly solved problem. Fun part is when you have to use all your cunning to gain that extra 1% accuracy.

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Metrics to Evaluate your Machine Learning Algorithm

Evaluating your machine learning algorithm is an essential part of any project. our model may give you satisfying results when evaluated against one metric but may give poor results when evaluated against other metrics. Read More

Training a Deep Learning Model on Handwritten charactersusing Keras

This is the first part of two part series on training your own model on handwritten characters. This part focuses on generating your own character dataset. In the next part, we will discuss, as how to create and train our own model.

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