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Hi, Sudhanshu1304 here 👋


About Me 👨‍🎓

Data Engineer @Bajaj Finserv Health

  • I Love Developing Products, and applying algorithms to different domains, specially the one using ML or AI concepts.
  • I write blogs on Machine Learning at Medium.
  • I enjoy Hackathons, as we get an opportunity to apply AI on real-life problems
  • I was a Machine Learning Engineer at Intellekt AI, where I am had experience with reinforcement learning in the finance domain..

My Recent Blogs

  • Recent Article 0
  • Multicollinearity

Social Profile 😏📕

  • 👨‍💻 All of my projects are available at Portfolio

  • 📄 Know about my experiences Resume

Connect with me:

sudhanshu-pandey-847448193 sudhupandey sudhanshu.dpandey

Languages and Tools:

django     docker     firebase     flask     git     javascript     linux     mysql     python     pytorch     tensorflow

Sudhanshu Pandey's Projects

2048_bot icon 2048_bot

Play 2048 On Computer and Beat The BOT if YOU Can.

a.i--hit__target icon a.i--hit__target

This is my First Self_Learning_Game_USING Logistic_Regression and PYGAME

autoencoders icon autoencoders

Autoencoder is an unsupervised Learning approach. It is an Artificial Neural Network(ANN) that learns to capture important piece of information (features) from a given data. An Autoencoder forms a representation of the actual data into a small matrix also known as latent space.

brain-mri-synthesis icon brain-mri-synthesis

A Research Project Using Generative models like Variational Autoencoder (VAE), T2-Weighted Images are being generated from T1-Weighted Images. Have achieved a maximum of 0.15 RMSE on validation dataset.

brain-tumor-segmentation icon brain-tumor-segmentation

Created a semantic segmentation model using PyTorch framework called MONAI. In this project I have applied various data augmentation technique and have build a UNet deep learning model.

covid_19-analysis icon covid_19-analysis

Predication on No_Of_Deaths In Maharashtra, Getting Data using Web_Scraping

customer_segmentation icon customer_segmentation

In large business firms, the major aspect to deal with is a large amount of data. One such aspect is "feedback from the customer". It uses Unsupervised Learning for Customer Segmentation and also performs Topic Modeling.

deskapp icon deskapp

Desktop 🖥 Application based on AI .A Productivity Tool, which uses AI to analyze User Activity. Users can learn where are they spending there time most and also compare amount of work done per day for months. It has different graphs to show our performance.

dockerizing-django-application icon dockerizing-django-application

Learn how to containerize your Django project using Docker, including two different methods: using only a Docker file or using Docker Compose. Explore the syntax of both approaches and discover how to make real-time changes to your dockerized application as you develop it locally.

fall-back-to-safe-zone icon fall-back-to-safe-zone

This is a concept that considers factors such as injured individuals, rescue teams, and people who are unaware of the threat and locates the safest safe zones, such as hospitals, and distributes injured into them.

machine-learns icon machine-learns

An Interactive Website to do hands-on Machine learning. An online platform for learning and visualizing machine learning and deep learning concepts. Here you can see algorithm in action. Examples: Read about Autoencoder and see how they work.

modelauto icon modelauto

Pip install ModelAuto ( ML Automation Library ) .A PyPI library used for automating model building task. It provides us helpfull tools to perform tasks like Data preprocessing, Feature selection and Model Selection with few lines of code.

music-genra-recognition icon music-genra-recognition

This is a simple speech recognition algorithm. This was a Learning Project, in which I learned how to apply machine learning to sounds, using concepts like Mfcc and the role of Fourier transform.

nueral_network_visualizer- icon nueral_network_visualizer-

Visualize the change like- "CHANGE IN THETA VALUES", "CHANGE IN ERRORS" ,"COST FUNCTION",CHANGE IN PREDICTION" with each ITERATION

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