singhsidhukuldeep

2D-Navier-Stokes-Solver

As the field of Computational Fluid Dynamics (CFD) progresses, the fluid flows are more and more analysed by using simulations with the help of high speed computers. In order to solve and analyse these fluid flows we require intensive simulation involving mathematical equations which governs the fluid flow, these are Navier Stokes (NS) equation. Solving these equations has become a necessity as almost every problem which is related to fluid flow analysis call for solving of Navier Stokes equation. These NS equations are partial differential equations so different numerical methods are used to solve these equations. Solving these partial differential equations so different numerical methods requires large amount of computing power and huge amount of memory is in play. Only practical feasible way to solve these equation is write a parallel program to solve them, which can then be run on powerful hardware capable of parallel processing to get the desired results High speed supercomputer will provide us very good performance in terms of reduction in execution time. In paper focus will be on finite volume as a numerical method. We will also see what GPGPU (General-Purpose computing on Graphics Processing Units) is and how we are taking its advantages to solve CFD problems.

Code-Editor

Code Editor Application that is platform independent i.e., download once and run anywhere.

Google-Colab-Shell

Now you can open shell in Google Collab

Recommendation-System

Comparing different recommendation systems algorithms like SVD, SVDpp (Matrix Factorization), KNN Baseline, KNN Basic, KNN Means, KNN ZScore), Baseline, Co Clustering

request-boost

A better requests and urllib. A simple package for hitting multiple URLs and performing GET/POST requests in parallel.

SimplexSolver

Using Simplex Algo. to solve Linear Optimization Problem.

singhsidhukuldeep.github.io

This is a completely open-source repo of interview questions and answers for people preparing for such interviews. This is maintained by you and you can send the questions that you faced during interviews.

stay-awake

Simple Platform Independent Python package to keep your system awake without affecting workflow!

Text-Summarizer

Comparing state of the art models for text summary generation

Youtube-Views-Hack

Increase Youtube Views with multiple videos playing at once and reloading at a set frequency

singhsidhukuldeep/Google-Colab-Shell

Now you can open shell in Google Collab

singhsidhukuldeep/request-boost

A better requests and urllib. A simple package for hitting multiple URLs and performing GET/POST requests in parallel.

singhsidhukuldeep/2D-Navier-Stokes-Solver

As the field of Computational Fluid Dynamics (CFD) progresses, the fluid flows are more and more analysed by using simulations with the help of high speed computers. In order to solve and analyse these fluid flows we require intensive simulation involving mathematical equations which governs the fluid flow, these are Navier Stokes (NS) equation. Solving these equations has become a necessity as almost every problem which is related to fluid flow analysis call for solving of Navier Stokes equation. These NS equations are partial differential equations so different numerical methods are used to solve these equations. Solving these partial differential equations so different numerical methods requires large amount of computing power and huge amount of memory is in play. Only practical feasible way to solve these equation is write a parallel program to solve them, which can then be run on powerful hardware capable of parallel processing to get the desired results High speed supercomputer will provide us very good performance in terms of reduction in execution time. In paper focus will be on finite volume as a numerical method. We will also see what GPGPU (General-Purpose computing on Graphics Processing Units) is and how we are taking its advantages to solve CFD problems.

singhsidhukuldeep/Youtube-Views-Hack

Increase Youtube Views with multiple videos playing at once and reloading at a set frequency

singhsidhukuldeep/stay-awake

Simple Platform Independent Python package to keep your system awake without affecting workflow!

singhsidhukuldeep/Text-Summarizer

Comparing state of the art models for text summary generation

singhsidhukuldeep/singhsidhukuldeep.github.io

This is a completely open-source repo of interview questions and answers for people preparing for such interviews. This is maintained by you and you can send the questions that you faced during interviews.

singhsidhukuldeep/Recommendation-System

Comparing different recommendation systems algorithms like SVD, SVDpp (Matrix Factorization), KNN Baseline, KNN Basic, KNN Means, KNN ZScore), Baseline, Co Clustering

singhsidhukuldeep/fast-api-template

FastAPI is a high performance simple framework for building APIs(Application Programming Interface).

singhsidhukuldeep/Mask-RCNN-Object-Detection

You can now build a custom Mask RCNN model using Tensorflow Object Detection Library! Mask RCNN is an instance segmentation model that can identify pixel by pixel location of any object.

singhsidhukuldeep/Live-Object-Detection-Tensorflow

singhsidhukuldeep/Facial-landmarks-recognition

Identifying faces in photos or videos is very cool, but this isn’t enough information to create powerful applications, we need more information about the person’s face, like position, whether the mouth is opened or closed, whether the eyes are opened, closed, looking up and etc.

singhsidhukuldeep/Fraud-Prediction

Fraud detection model for synthetic dataset of money transactions.

singhsidhukuldeep/NLP-pipeline-using-Spacy

Natural Language Processing, or NLP, is the sub-field of AI that is focused on enabling computers to understand and process human languages.

singhsidhukuldeep/random-stock-picker

Random stock picker for Indian and US stock exchanges, NSE, BSE, NASDAQ, NYSE

singhsidhukuldeep/TRex-Neural-Network-AI

A simple artificial intelligence to teach Google Chrome's offline dinosaur to jump cactus, using Neural Networks and a simple Genetic Algorithm.

singhsidhukuldeep/ChatBot-using-Chatterbot

Creating Chatbot using Chatterbot in under few minutes

singhsidhukuldeep/Cognitive-Literature-Analysis

Cognitive Literature Analysis. This is submission for Microsoft ACAD Accelerator 2018

singhsidhukuldeep/contextual-bandits

A comprehensive Python library implementing a variety of contextual and non-contextual multi-armed bandit algorithms—including LinUCB, Epsilon-Greedy, Upper Confidence Bound (UCB), Thompson Sampling, KernelUCB, NeuralLinearBandit, and DecisionTreeBandit—designed for reinforcement learning applications

singhsidhukuldeep/Generating-Devanagari-Using-DRAW

PyTorch implementation of DRAW: A Recurrent Neural Network For Image Generation

singhsidhukuldeep/Mytrah-PCGT

Mytrah Energy Ltd. The objective of the PCGT Portal is to ease the process of comparing the power curve from site and the comparing of that with the one from the actual site of deployment. The software compiles the provided raw data by performing various filtration processes as well as the required calculations to get the Power Curve.

singhsidhukuldeep/Tensorflow-Eager-Execution

Eager Execution enables you to run operations immediately

singhsidhukuldeep/Text-Classification-using-FastText

Building the User Review Model with fastText (Text Classification) with response time of less than one second

singhsidhukuldeep/addons

Useful extra functionality for TensorFlow 2.x maintained by SIG-addons

singhsidhukuldeep/financial-demo

A demo for a financial services bot

singhsidhukuldeep/pdf-to-csv

Convert pdf to csv

singhsidhukuldeep/ranking_validation

A Framework for validating two ranked lists using ndcg, kendall's tau, rbo, recall, mrr

singhsidhukuldeep/skops

skops is a Python library helping you share your scikit-learn based models and put them in production

singhsidhukuldeep/template-python-django

A Django template, configured for Gitpod (www.gitpod.io) to give you pre-built, ephemeral development environments in the cloud.

singhsidhukuldeep/training-BERT-from-scratch

RoBERTa: A Robustly Optimized BERT Pretraining Approach. It builds on BERT and modifies key hyperparameters, removing the next-sentence pretraining objective and training with much larger mini-batches and learning rates.