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Dr. Joyjit Chatterjee's Projects

atm-machine-implementation icon atm-machine-implementation

The Program implements an ATM Machine in C++ which is capable of performing the following functions:- 1. Withdraw Money 2. Deposit Money 3. Create New Account This C++ Program makes use of Constructors (Default and Parameterized), Switch Conditional Statement, Functions and Do-While Loop.

deeplearning-tensorflow-basics icon deeplearning-tensorflow-basics

This repository contains basic Python code for learning to use Tensorflow, along with its basic syntactic and operational intricacies, as a solid foundation for other complex Deep Learning projects.

deeprlturbinevesseltransfer icon deeprlturbinevesseltransfer

Supplementary material for our paper "Deep Reinforcement Learning for Maintenance Planning of Offshore Vessel Transfer" in submission to RENEW 2020, Lisbon, Portugal.

email-summarization icon email-summarization

A module for E-mail Summarization which uses clustering of skip-thought sentence embeddings.

english2cypher icon english2cypher

A model to transform english into Cypher queries, based off the CLEVR-graph dataset

infer icon infer

A static analyzer for Java, C, C++, and Objective-C

java icon java

All Algorithms implemented in Java

martinheinz icon martinheinz

My GitHub Profile README. Don't just fork, star it, so others can find it too! 👀

movie-storage-system icon movie-storage-system

This is an implementation of a Movie Storage System in Python making extensive use of conditionals, list comprehensions, functions and loops. Note: This program is my solution to the programming exercise in the Complete Python Course: Learn Python by Doing, by Rob Percival.

refreshingcpp-skills icon refreshingcpp-skills

Mastering C++ for developing sophisticated software programs through ProceduralProgramming

scientometricreview-ai icon scientometricreview-ai

Data for our paper "Scientometric Review of Artificial Intelligence for Operations & Maintenance of Wind Turbines: The Past, Present and Future".

searchinsidepythonfiles icon searchinsidepythonfiles

Code to search inside Python files recursively to find a specific piece of string/text inside the files, when you get lost!

stock-prediction-models icon stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stockpredictionai icon stockpredictionai

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.

text2speech-python icon text2speech-python

Colab provides an interactive platform to execute your Python Scripts and AI Algorithms, but what if you want a speech output instead of Console Text? This repo helps you do exactly that, in a simple and concise way.

trackchanges-latex icon trackchanges-latex

Utilising the pdflatex utility on the terminal/command prompt to derive tracked changes between 2 versions of Tex files

treegen icon treegen

A Tree-Based Transformer Architecture for Code Generation. (AAAI'20)

tsfresh icon tsfresh

Automatic extraction of relevant features from time series:

turbinemaintenancetemplates icon turbinemaintenancetemplates

This repository contains human-authored corpus of maintenance actions for faults in offshore wind turbines. It includes:-

turbinescadacausality icon turbinescadacausality

Supplementary material for our TORQUE 2020 Submission "Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI"

vedic-binary-multiplier icon vedic-binary-multiplier

The project involved design of a Binary Multiplier which is highly efficient in terms of computation time and used the centuries old Urdhava-Tiryakbham algorithm. Structural Coding was used to first design a 2 bit Vedic Binary Multiplier in VHDL using Half Adders. Then, generic adders along with the 2 bit multiplier blocks designed initially was used to simulate a 4 bit Vedic Binary Multiplier.

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