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joyjitchatterjee

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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.

XAI4Wind

Supplementary data for utilising knowledge graph databases towards explainable decision support in wind turbines.

Python

WindTurbine-QAKG

Automated Question-Answering Over Knowledge Graphs in O&M of Wind Turbines

Python

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.

Jupyter Notebook

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.

VHDL

TurbineSCADACausality

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

ScientometricReview-AI

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

TeX

joyjitchatterjee/DeepLearning-Tensorflow-Basics

joyjitchatterjee

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