Anand P V (AdroitAnandAI)

AdroitAnandAI

Geek Repo

Company:KLA-Tencor

Location:Chennai

Home Page:https://anandai.medium.com/

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Anand P V's repositories

Indian-Accent-Speech-Recognition

Traditional ASR (Signal & Cepstral Analysis, DTW, HMM) & DNNs (Custom Models + DeepSpeech) on Indian Accent Speech

Language:Jupyter NotebookLicense:CC0-1.0Stargazers:84Issues:5Issues:8

SLAM-on-Raspberry-Pi

Robotic Localization with SLAM on Raspberry Pi integrated with RP LIDAR A1. Point Cloud remote visualization doing using MQTT in real-time.

Language:Jupyter NotebookLicense:CC0-1.0Stargazers:47Issues:3Issues:1

Self-Driving-Car-on-Indian-Roads

Computer Vision Guided Deep Learning Network & Machine Learning Techniques to build Fully-Functional Autonomous Vehicles

Language:PythonStargazers:30Issues:1Issues:0

ADAS-Car-using-Raspberry-Pi

ADAS Car - with Collision Avoidance System (CAS) - on Indian Roads using LIDAR-Camera Low-Level Sensor Fusion. DIY Gadget built with Raspberry Pi, RP LIDAR A1, Pi Cam V2, LED SHIM, NCS 2 and accessories like speaker, power bank etc

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LSTM-Attention-based-Generative-Chat-bot

Personified Generative Chatbot using RNNs (LSTM) & Attention in TensorFlow

Language:Jupyter NotebookStargazers:22Issues:1Issues:3

Algo-Trading-Math-Models

Math Techniques viz. ARIMA, Frequency Decomposition, Fourier Filtering, Linear Regression & Bi-directional LSTMs on Feature Engineered Stock Market Data.

Language:Jupyter NotebookStargazers:18Issues:3Issues:0

Topic-Modelling-LDA-NMF-W2V

Numerical combination of LDA and NMF cascaded with W2V to categorize 1M+ multi-lingual records into a 275-node, 5-level deep category tree.

Language:Jupyter NotebookStargazers:11Issues:2Issues:0

Facial-Attendance-on-Pi-with-LIDAR

Face Recognition-based Attendance system deployable on Raspberry Pi with Movidius NCS2. RPLIDAR A1 is integrated for depth sensing to enable Door Access Control simulated with Pimoroni Blinkt!

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Multilingual-Text-Inversion-Detection-of-Scanned-Images

Efficient Text Localization Algorithm, Image Inversion Detection of Scanned Documents & Language Identification based on Shape Context and Traditional Computer Vision.

Language:PythonLicense:GPL-3.0Stargazers:8Issues:2Issues:0

No-Touch-Display-Interface-at-Edge-IoT

Enabling HCI on the Edge: Gesture & Offline Sound Control of kiosks with AI models, hardware optimized with Intel OpenVINO, code optimized with VTune

Language:PythonStargazers:8Issues:2Issues:0

Object-Detection-on-Mobile-Cam-for-Blind

Multi-Class Object Detection on Mobile Video Stream, using Deep Learning ConvNets, to assist the blind or to signal an incoming threat, without radars.

Language:PythonStargazers:6Issues:1Issues:0

Computer-Vision-Math-Magic-vs-AI

Computer Vision for Skew Correction, Text Inversion, Rotation Classification, Homography & Object Search with Applied Math

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ML-Algorithms-in-MATLAB

MATLAB Code for Linear & Logistic Regression, SVM, K Means and PCA, Neural Networks Learning, Multiclass Classification, Anomaly Detection and Recommender systems.

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Indoor-Navigational-Assistance-with-RPi-and-Mobile

Indoor Navigational Assistance with Custom Object Detection and SLAM on Raspberry Pi and Android Mobile

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Scalable-ML-with-Spark

Scalable Machine Learning using Spark MLlib on Standalone, AWS EMR Cluster with Docker & Nvidia RAPIDS Accelerator mode.

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Automated-Reasoning-with-ML-Knowledge-Graph-and-Machine-Comprehension-with-AI

Machine Automated Reasoning using Grakn KGLib, Knowledge Graph Convolutional Networks (KGCNs) & Machine Comprehension using BERT-BIDAF-Ensemble

Language:PythonStargazers:1Issues:2Issues:0

Clustering-on-Word-Vectors-using-Truncated-SVD

Semantic clustering of text using K-means on custom-built contextual Word Co-occurence matrix, decomposed using SVD. Truncated length of word vectors are estimated by plotting explained variance of decomposed matrix.

Language:Jupyter NotebookStargazers:1Issues:1Issues:0

CNN-Architectures-for-Handwritten-Image-Classification

To classify images containing handwritten digits using multiple custom-built CNN architectures, which may or may not are inspired from standard Convnet architectures such as LeNet, AlexNet, VGGNet, ResNet etc. A comparison between performance of different architectures are done.

Language:Jupyter NotebookStargazers:1Issues:1Issues:0

Gesture-Triggered-Alarm-on-Pi-or-Jetson-Nano

Gesture Triggered Alarm for Women Security based on Computer Vision, Mathematical Concavity Estimation, MQTT, OpenVINO and Pimoroni Blinkt! on RPi or Jetson Nano

Language:PythonLicense:CC0-1.0Stargazers:1Issues:2Issues:0

K-Means-Hierarchical-DBScan-Clustering-Analysis

Hyperparameter Tuning of K-Means using Elbow Method, Eps values based on MinPoints for DBScan and Hierarchical Clustering based on various values of 'k' is done to form different clusters, on which an analysis is done for semantic coherence.

Language:Jupyter NotebookStargazers:1Issues:1Issues:0

Multiple-MLP-Architectures-on-MNIST-database-using-Keras

To use different MLP architectures having different number of layers on the famous MNIST database. Tweaking methods like dropouts, batch normalization are applied and cross entropy loss is being tracked for analysis and comparison between architectures.

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cand-c2-project

Design, Provision and Monitor AWS Infrastructure at Scale. Cloud Architect Nano-degree

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ChatCrazie

A chatbot implemented using RNN and GloVe embeddings whch answers your query crazily

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Decision-Trees-Analysis-on-BoW-tf-idf-W2V-tf-idf-weighted-W2V

To analyze the performance of DT on BoW, tf-idf, W2V & tf-idf weighted W2V featurizations of Amazon Reviews data. Tree depth is taken as the hyperparameter tuned using GridSearchCV. The similarity in shape of CV Error vs Depth plots across all featurizations is noticeable.

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GBDT-and-Random-Forest-Classifier

Gradient Boosted Decision Tree & Random Forest Classifier on high dimensional data

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Multi-Class-Sentimental-Analysis-Deep-Learning

5-class Sentimental Analysis using various LSTM Architectures to draw comparisons

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nd063-c3-design-for-security-project-starter

Starter code for Course 3 of nd063

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Parallel-RNG-using-GPU

Parallel implementation hack of inherently sequential algorithms. Random Number Generators - Additive LFG and GFSR - implemented with NVIDIA CUDA using Continuous Subsequence Technique and Leap Frog Technique. Paper presented in the International AI Conference 2022, Tel Aviv, Israel.

Language:CudaLicense:GPL-3.0Stargazers:0Issues:2Issues:0

Question-Answering-MRC-with-AI

Machine Reading Comprehension on Chatbots using BiDAF-Glove

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tensorflow

An Open Source Machine Learning Framework for Everyone

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