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AI Engineer, Tech Geek, and a Passionate Programmer!

Hi, I'm MageshAI Engineer Focused on building real-time AI solutions.

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Hats:

Current Role: Senior AI Consultant @AstraZeneca - AI/NLP/MLOps for research in Pharmaceutical Industry

Machine Learning Engineer @yougroup.io - NLP, Data Infra for Tourism Metasearch

AI Engineer @Concord - NLP, Computer Vision for Document Intelligence

Computer Vision Engineer @WIPRO - ADAS L3

ML Engineer @WIPRO - Fullstack Datascience

AI Solutions:

Tourism Industry:

NLP: Multi-lingual Sentiment Analysis on Tourism Data

NLP: Semantic Similarity / Search on Tourism Data

NLP: Machine Translation

CV: User Demographics Analysis(Age, Gender)

Document Intelligence Solutions:

NLP: NER and Text Classification on Scanned Healthcare Documents

CV: Layout Analysis, OCR and Table Extraction from Scanned Documents

ADAS Solutions:

CV: Object Detection, Lane Segmentation, Traffic Sign Recognition

Skills:

Deep Learning || NLP || MLOps || Computer Vision || Datascience

ETL || PySpark

Pytorch || Tensorflow || Transformers || spaCy || OpenCV

Serverless || Airflow || Docker || Microservices || Kubernetes

AWS || Azure || GCP

Familiar AI Tasks:

Natural Language Processing:

Named Entity Recognition

Semantic Search

Machine Translation

Text Classification

Computer Vision:

Optical Character Recognition (OCR)

Segmentation

Object Detection

Image Classification

Love To:

CODE, Read Books

Understand Human Brain, Psychology

Build Products

Open-source Tech Hacks

Read & write TECH BLOGS

AI Blogs:

Artificial Intelligence and the evolution of Homo Deus --Insights on How AI is impacting billions of Lives today

How businesses use AI to thrive in the digital economy --A Comprehensive survey on business use cases of AI and how AI is impacting lives of billions

How far are we from replicating the Human Brain into a Computer? --Introduction to astounding facts about the Human Brain and comparing them with recent advancements in AI

CV Blogs:

Everything You Need to Know About Image Segmentation --A Comprehensive survey on Image Segmentation

Semantic Segmentation using DeepLabV3

OCR:

Scene Text Detection In Python with EAST and CRAFT

Improving OCR Accuracy with Image preprocessing

NLP Blogs:

Topic Modeling: Art of Storytelling in NLP --Survey on Topic Modeling LSA, pLSA, LDA with implementation in python

Multi-label text classification --Survey on Multi-label text classification, with detailed explanation and implementation of various Machine algorithms, problem transformation and evalution metrics

Mageshwaran R's Projects

deep-learning-in-production icon deep-learning-in-production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

detr icon detr

End-to-End Object Detection with Transformers

doctr icon doctr

The official code for “DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction”, ACM MM, Oral Paper, 2021.

docvqa icon docvqa

Document Visual Question Answering

ml-from-scratch icon ml-from-scratch

Machine Learning From Scratch. Bare bones Python implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from data mining to deep learning.

oscar icon oscar

Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

publaynet icon publaynet

MaskRCNN on PubLayNet datasets. Paragraph detection, table detection, figure detection,...

python icon python

All Algorithms implemented in Python

real-time-ml-project icon real-time-ml-project

A curated list of applied machine learning and data science notebooks and libraries across different industries.

stockpredictionai icon stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

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