aigerimhatake

AMAW-PINN

Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting

Amusive-Blogging-N-Coding

Open source code from the blog posts at

Churn_prediction_using_logistic_regression

Predicting customer churn with logistic regression by applying Synthetic Minority Oversampling Technique and Recursive Feature Elimination

Complex-valued-NNs

Customer_segmentation

Create and analyze customer segments with k-means clustering

Customer_segmentation_Arvato

k-means clustering, XGBClassifier and Gradient Boosting for customer segmentation and acquisition

D-Wave

quantum experiments using D-Wave

Deep_Matrix_Factorization_Models

Implementation of the "Deep Matrix Factorization Models for Recommender Systems"

DeepPavlov

An open source library for deep learning end-to-end dialog systems and chatbots.

ev-charger-placement

Determine where to place new charging stations on a map based on locations of existing charging stations and points of interest.

aigerimhatake/AMAW-PINN

Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting

aigerimhatake/Amusive-Blogging-N-Coding

Open source code from the blog posts at

aigerimhatake/D-Wave

quantum experiments using D-Wave

aigerimhatake/DeepPavlov

An open source library for deep learning end-to-end dialog systems and chatbots.

aigerimhatake/ev-charger-placement

Determine where to place new charging stations on a map based on locations of existing charging stations and points of interest.

aigerimhatake/gradient-descent-notebook

Repository for storing the notebook for gradient descent in the context of linear regression.

aigerimhatake/idrlnet

IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.

aigerimhatake/Line-up-optimization

Optimize the initial line-up of Liverpool FC using the LeapHybridSampler.

aigerimhatake/MSc-Thesis

aigerimhatake/MultiscalePINNs

aigerimhatake/Numerical_Quantum_Computing

numerical_computing_qubo

aigerimhatake/penaltymodel

Utilities and interfaces for using penalty models.

aigerimhatake/pennylane

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.

aigerimhatake/Physics-Informed-Neural-Networks

Investigating PINNs

aigerimhatake/PINN

Simple PyTorch Implementation of Physics Informed Neural Network (PINN)

aigerimhatake/PINNs-3

aigerimhatake/PINNs-TF2.0

TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).

aigerimhatake/practical-recommender-systems

aigerimhatake/Predict_CLTV_with_linear_regression

Utilize linear regression to predict Customer Lifetime Value and develop positive ROI strategies

aigerimhatake/Predict_customer_churn_multilayer_perceptron

Predict customer churn using sequential neural network

aigerimhatake/Predict_next_month_transactions

Recency, Frequency, Monetary metrics to forecast customer behaviour with linear regression

aigerimhatake/Project1

Course Assignments

aigerimhatake/pyqubo

Python DSL for constructing QUBOs from mathematical expressions.

aigerimhatake/qbsolv

Qbsolv,a decomposing solver, finds a minimum value of a large quadratic unconstrained binary optimization (QUBO) problem by splitting it into pieces solved either via a D-Wave system or a classical tabu solver. (Note that qbsolv by default uses its internal classical solver. Access to a D-Wave system must be arranged separately.)

aigerimhatake/qibo

A framework for quantum computing

aigerimhatake/Quantum-Linear-Regression

aigerimhatake/qutip-lectures

Lectures on QuTiP: slides and ipython notebooks

aigerimhatake/SA-PINNs

Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]

aigerimhatake/sciann

Deep learning for Engineers - Physics Informed Deep Learning

aigerimhatake/Tutorials

Code for some of my tutorials