Discover @AdroitAnandAI Open Source projects

Anand P V (@AdroitAnandAI)

AdroitAnandAI

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312
Global Rank 86,263 (Top 3 %)
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Registered over 6 years ago
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Python
45.5 %

Jupyter Notebook
45.5 %

HTML
4.5 %

MATLAB
4.5 %
Location 🇮🇳 India
Country Total Rank 2,946
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Jupyter Notebook
196

MATLAB
469

Python
1,023

HTML
9,593

Indian-Accent-Speech-Recognition

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

Jupyter Notebook

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.

Jupyter Notebook

Self-Driving-Car-on-Indian-Roads

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

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

LSTM-Attention-based-Generative-Chat-bot

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

Jupyter Notebook

Algo-Trading-Math-Models

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

Jupyter Notebook

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.

Jupyter Notebook

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

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!

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.

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.

Computer-Vision-Math-Magic-vs-AI

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

Crime-Analysis-Prediction

Linear Model to predict the crime rate of North Carolina. Detailed EDA done prior to building model

Jupyter Notebook

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.

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

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

Scalable-ML-with-Spark

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

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

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

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.

Jupyter Notebook

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.

Jupyter Notebook

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.

Jupyter Notebook

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.

Jupyter Notebook