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cuda-quantum

C++ and Python support for the CUDA Quantum programming model for heterogeneous quantum-classical workflows

cumupy

A python code to compute the cumulante expansion of the Green's function for photoemission spectroscopy

curie_weiss_periodic

Exact Dynamics of Periodically driven Curie Weiss Spins

custom-poling

Module for designing the domain configuration of a nonlinear crystal to approximate a desired phase-matching function.

cyber-security-cryptographic-correlation-power-analysis

This project is about performing a power-side channel attack over a practical implementation of a cryptographic algorithm. My team attempted to recover the secret key used for the cryptographic algorithm from the collected power measurements. We specifically use a technique called Correlation Power Analysis (CPA) to recover the secret key.

cyclegan-with-self-attention

In this repository, I have developed a CycleGAN architecture with embedded Self-Attention Layers, that could solve three different complex tasks. Here the same principle Neural Network architecture has been used to solve the three different task. Although truth be told, my model has not exceeded any state of the art performances for the given task, but the architecture was powerful enough to understand the task that has been given to solve and produce considerably good results.

dall-e

PyTorch package for the discrete VAE used for DALL·E.

data-science-best-resources

Carefully curated resource links for data science in one place

data-science-hackathon

Data Science Hackathon

data-science-hackathon-and-competition

Grandmaster in MachineHack (3rd Rank Best) | Top 70 in AnalyticsVidya & Zindi | Expert at Kaggle | Hack AI

data-science-interview-preperation-resources

Resoruce to help you to prepare for your comming data science interviews

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data-scientist-roadmap

Toturials coming with the "data science roadmap" picture.

data-structures-algorithms-python

This tutorial playlist covers data structures and algorithms in python. Every tutorial has theory behind data structure or an algorithm, BIG O Complexity analysis and exercises that you can practice on.

data_science_blogs

A repository to keep track of all the code that I end up writing for my blog posts.

databricks-azure-digital-twin

datascienceresources

Open Source Data Science Resources.

david-silver-reinforcement-learning

Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.

dcgan

A Jupter Notebook containing the code and explanations from the PyTorch implementation of Deep Convolutional Generative Adversarial Networks.

dcgan-oreilly

Notebook for O'Reilly's "Deep Convolutional Generative Adversarial Networks"

dcgan_tensorflow

Notebook for a Deep Convolutional Generative Adversarial Network implemented using TensorFlow in Python

dcgans

Notebook for #Deep Convolutional Generative Adversarial Networks"

dd-quantum-measurements

Sample from Quantum Hamiltonians using decision diagrams

ddsim

MQT DDSIM - A quantum circuit simulator based on decision diagrams written in C++

decision-tree

This notebook is related to decision tree algorithm and how to deal with overfitting and perform pruning(Pre Pruning) in decision tree

decision-tree-titanic-survival-prediction

In this notebook, I explore decision trees and how pruning can improve the decision tree accuracy scores. I also show how creating a validation set can be helpful towards building a good ML model. The decision tree ML model can predict whether or not a person will survive based on several features in the data set.

decision_tree_adventures

Group of notebooks about decision trees. It starts with the simplest one and then continues with the mechanism, tuning, pruning and comparison of decisin trees.

deep-convolution-generative-adversarial-networks

This repository contains my ipynb notebook for implementing Deep Convolution Generative adversarial networks.We used MNIST images to train the DCGAN

deep-learning

Course: Deep Learning

deep-learning-1

Repo for the Deep Learning Nanodegree Foundations program.