starkgit91
As an intermediate in DSA, I'm passionate about finding optimal solution to complex problems. Intern at IIT Kanpur AI&ML | DSA | Codeforces 500+ problems solved
NIT Andhra
Pinned Repositories
Binary-Classification-using-LogisticRegression
CNN-GaussNoiseAttack-Classification
Binary Classification of Future Data with 0.9781 Score with Accuracy is nearly 0.96 and loss function 0.22.
CNN-TimeSeriesClassification
Codeforces-Solutions
Here I have dumped most of the solutions of problems on Codeforces under the contest Educational Round, DIv2, Div3,Div1+Div2, CodeTon,CodeCraft-25 etc.
LSTM-Gauss-Noise-Attack-TimeSeries-Classification
Gauss Noise Attack Classification with Non Guassian Time Series Data Using LSTM Neural Nets Artitecture with an Accuracy 0f 0.97 and loss function of 0.14. Binary Classification of predicted New Data having accuracy 0.99.
LSTM-Target-Defense-IEEEBUS-Case14-FDI
LSTM-Time-Series-Forecasting
Maximum-Independent-Set-MIS
DSA- Graph Algorithm and MIS Implementation using OpenAI's gym package
RL-gym-env-Automation
Automation of GridWorld Environment at any Random State Space/ Markov's Decision Process(MDP) automation using RL Model DQN and A2C and OpenAI's gym library. For every reward the agent will et +10 and for every peanlty agent will get -100, -10 for differed case like "*".
Visual-Power-Grid
Power System simulation tool to visualize the steady state power system operation, such as optimal power flow and state estimation. The functions also include generating false data injection (FDI) attacks and detect by using Moving Target Defence (MTD).
starkgit91's Repositories
starkgit91/LSTM-Gauss-Noise-Attack-TimeSeries-Classification
Gauss Noise Attack Classification with Non Guassian Time Series Data Using LSTM Neural Nets Artitecture with an Accuracy 0f 0.97 and loss function of 0.14. Binary Classification of predicted New Data having accuracy 0.99.
starkgit91/RL-gym-env-Automation
Automation of GridWorld Environment at any Random State Space/ Markov's Decision Process(MDP) automation using RL Model DQN and A2C and OpenAI's gym library. For every reward the agent will et +10 and for every peanlty agent will get -100, -10 for differed case like "*".
starkgit91/Binary-Classification-using-LogisticRegression
starkgit91/CNN-GaussNoiseAttack-Classification
Binary Classification of Future Data with 0.9781 Score with Accuracy is nearly 0.96 and loss function 0.22.
starkgit91/CNN-TimeSeriesClassification
starkgit91/LSTM-Target-Defense-IEEEBUS-Case14-FDI
starkgit91/LSTM-Time-Series-Forecasting
starkgit91/Maximum-Independent-Set-MIS
DSA- Graph Algorithm and MIS Implementation using OpenAI's gym package
starkgit91/Visual-Power-Grid
Power System simulation tool to visualize the steady state power system operation, such as optimal power flow and state estimation. The functions also include generating false data injection (FDI) attacks and detect by using Moving Target Defence (MTD).
starkgit91/Codeforces-Solutions
Here I have dumped most of the solutions of problems on Codeforces under the contest Educational Round, DIv2, Div3,Div1+Div2, CodeTon,CodeCraft-25 etc.
starkgit91/DSA-Implementations
starkgit91/starkgit91
Config files for my GitHub profile.