Name: Prashant Sridhar
Type: User
Company: Software Dev Lead @launchpointlimited, previously at @periwinkletrading.
Bio: Machine Learning Engineer by day. Modular Synth enthusiast by night.
Currently spending time figuring out the fun world of Rust.
Location: Hong Kong
Blog: https://www.linkedin.com/in/prashant-sridhar/
Prashant Sridhar's Projects
Abnormality Detection in Musculoskeletal Radiographs
Curated applications for Kubernetes
Coingecko API python wrapper and associated token data retrieval and qualtiative analysis. Used in https://echoplace.medium.com/a-very-brief-survey-of-the-altcoin-landscape-3ca362be3ae9
Final Notebook for the Course Project of CS4487. All done on Colab.
Deep Learning tutorials in jupyter notebooks.
An alternative way to work on something I previously "worked" on
figuring out GANs
Playing around with Google Earth Engine
Vision in Greek, simple object detection application built for the iOS
Experimentation of Deep Learning Models for Medical Imaging.
CNNs for Malaria
A boilerplate, for running Prisma behind a graphql endpoint, inside Docker
Artificial Neural Networks using Genetic Algorithms
Scraper written in R for SSCAC
Suite of techniques to help improve a potential prediction of a price for a stock.
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
A project where the intention is to develop a Genetic Algorithm to solve the Symmetric Travelling Salesman Problem.
Telegraf local sessions middleware with multiple supported storage types (Memory/FileSync/FileAsync/...) using lowdb
A paradigm for financial applications. Reference implementation in Python. #EleNão