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  • šŸ‘‹ Hi, Iā€™m @faisalnazir
  • šŸ‘€ Iā€™m interested in Machine Learning, Quantum Computing and Blockchain especially Ethereum and its layer 2s.
  • šŸŒ± Iā€™m currently learning Financial Quantative Analysis.
  • šŸ’žļø Iā€™m looking to collaborate on - developing a DAPP and a Decentralised Exchange.
  • Started to get deep into Digital Twins
  • šŸ“« How to reach me ... find me on linkedin.

faisalnazir's Projects

amazon-sagemaker-examples icon amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

aws-cloudformation-publisher icon aws-cloudformation-publisher

AWS CloudFormation Publisher packages your CloudFormation templates into an S3 bucket in every AWS region and creates "launch stack" links that you can use in your documentation so that your customers can easily launch stacks in their AWS accounts from your CloudFormation template.

enet icon enet

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

eth-price-prediction icon eth-price-prediction

Predicting Ethereum price changes. Results of an LSTM (Long Short Term Memory) and an SVM (Support Vector Machine) are being compared.

face-api.js icon face-api.js

JavaScript API for face detection and face recognition in the browser with tensorflow.js

lambda-refarch-imagerecognition icon lambda-refarch-imagerecognition

The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.

ml-from-scratch icon ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

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