vatsl/songPopularity

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Python
Created over 8 years ago
Updated over 7 years ago

vatsl/songPopularity

vatsl

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An app to scrape the Rammstein's song's translation requests and gauge their popularity from it.

TrafficLight_Detection-TensorFlowAPI

Traffic Light Detection and Classification using TensorFlow Object Detection API

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An implementation of the Particle Filter using C++ for the purposes of localization.

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Implementation of Model Predictive Control to autonomously navigate a vehicle.

AutonomousDriving

A few projects towards gaining knowledge of developing autonomous vehicles using Computer Vision and Deep Learning.

Jupyter Notebook

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Build a path planner that creates smooth and safe trajectories for the car to follow.

DeepLearning-ND101

Projects to learn the concepts of Deep Learning like CNN, RNN, LSTM, GAN, etc.

Jupyter Notebook

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Determining the steering angle of an autonomous vehicle using the concepts of PID controllers.

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An end-to-end automatic speech recognition (ASR) pipeline with a deep neural network. The pipeline accepts raw audio as input and return a predicted transcription of the spoken language.

ExtendedKalmanFilter

An implementation of Extended Kalman Filter for pedestrian detection using Lidar and Radar data.

gi-remotes

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Isolation-GamePlaying

Building a game playing AI agent to win at the game of Go.

SudokuSolver

Learn the basic techniques in Artificial Intelligence like Search and Constraint Propagation by creating a program to solve a Sudoku problem.

MIT60001

Code for assignments of MIT's 6.0001 - Introduction to Computer Science and Programming in Python

SignLanguageRecognizer

Build a system that can recognize words communicated using the American Sign Language (ASL) using a preprocessed dataset of tracked hand and nose positions extracted from video. The goal is to train a set of Hidden Markov Models (HMMs) using part of this dataset to try and identify individual words from test sequences.

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Define a group of problems in classical PDDL (Planning Domain Definition Language) for the air cargo domain. Set up the problems for search, experiment with various automatically generated heuristics, including planning graph heuristics, to solve the problems.