Profile

Aditya Vikram Singh

Data Scientist | Machine Learning Engineer | Data Analyst |

Aditya Vikram Singh is a highly skilled and competent Data Scientist, Machine Learning Engineer, and Data Analyst with over 2 years of experience. He possesses expertise in a range of machine learning techniques including logistic regression, SVM, decision tree, random forest, GBDT, CNN, R

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4.7

Years of Experience

Education

bml munjal university, lucknow public school, saraswati vidhya mandir

Companies

matrixcare, bytelearn, paralleldots, rdiger whrl gmbh, edgistify, applied ai course

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Aditya Vikram's contact details

Email

Email (Verified)

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Email

Mobile Number

+9XXXXXXXXX75

Experience

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    2022 - Present

    matrixcare

    Data Scientist

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    2021 - 2022

    bytelearn

    Data Analyst

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    2021 - 2021

    paralleldots

    Backend Developer

    Developed and maintained APIs -> Developed and maintained 20+ APIs for the company's website and business team. The use of APIs by the business team (to get required data) benefited both the tech and business team because the earlier business team used to ask for data from the backend (tech) team. Query Optimization -> Optimized SQL queries for heavy load parts of the system, which improved website responsiveness. Designed Algorithm for Giving Proper Indexing -> Designed and implemented an algorithm that can give proper indexing (shelf number, row number, and stack layer) for products over shelves.

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    2020 - 2021

    rdiger whrl gmbh

    Data Scientist

    ANPR: Automatic Number Plate Detection (Python, YOLO-V4, CRAFT, CRNN) -> Detecting the license plate number of vehicles of all European countries. Deployed the model on RPi4 and ODroid board. The accuracy of ANPR (deployed on RPi4) is 94% of accuracy. It can detect the all special character of German alphabets and other special characters of European countries. This ANPR is capable of recognizing the country of vehicle by looking at its license plate. Currently working on the premium version of this ANPR. Container Number Detection (Python, YOLO-V4, CRAFT, Classifier) -> Detecting the container number of shipping containers and deployed the model on RPi4 and ODroid board. The overall accuracy of this model is 95%.

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    2020 - 2020

    edgistify

    Data Scientist

    1. Extracting Warehouse Availability/To-Let Information from Newspapers (Python, YOLO-V4, OpenCV, Pytesseract) -> Extracting the warehouse availability/to-let information from advertisement section of the newspapers. Used custom trained YOLOv4 to locate & find the box around the advertisement sections and then applied images-processing techniques like canny-edge detection, dilation, contours, etc. to find the boxes around each ad. Passed the cropped advertisement section in Pytesseract model for OCR and then applied the text processing techniques to extract the required data. 2. Extracting the Location (i.e. Lat & Long) of Warehouses from Google-Map (Python, YOLO-V4, OpenCV, Selenium) -> Extracting the exact location (i.e. latitude and longitude) of warehouses from Google-Map in a given region of India. Used custom trained YOLOv4 model with manually labeled dataset to locate & find the box around warehouse/s in image of Google-Map. Used Selenium to click at a specific location (obtained from YOLO), to get the location of warehouse from Google-Map and to move the map in a defined region. 3. Building the Warehouse Database (Python, BeautifulSoup, Selenium, Pandas) -> Created the database of the warehouse availability, warehouse details, customer details, agent details for all states of India from various websites.

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    2019 - 2020

    applied ai course

    Machine Learning Engineer

    1. Toxic Comment Classification and Unintended Bias Reduction (DL/ML, Keras, TensorFlow, Scikit-Learn, Python) -> The dataset has toxic and non-toxic comments. Given a comment model must find the toxicity and reduce the unintended bias. Various ML and DL models (like logistic regression, random forest, Bi-directional GRUs, etc.) were used and then stacked the good performing models. It can be used in online discussion forums. -> Blog: https://medium.com/datadriveninvestor/jigsaw-unintended-bias-in-toxicity-classification-d9adf34307d3 2. Question-Answering System similar to Simple Search Engine (DL/ML, Keras, TensorFlow, Scikit-Learn, Python) -> In the dataset there are 10 answers for each question but only one of them is correct. For a given pair of question and answer model must predict whether it is correct or not. The best model was selected to calculate the MRR (mean reciprocal rank) on test data. Various DL/ML models (like logistic regression, random forest, Bi-directional GRUs, etc.) were used. -> Blog: https://medium.com/@singhadityastudy/simple-search-engine-9062a644da5c?source=friends_link&sk=a2ee7211f6b812a5b8f0039b4c9eb84d

Experience

103 Skills

Amazon Web Services (AWS)

Application Programming Interfaces (API)

architecture

Artificial Intelligence (AI)

Artificial Intelligence (AI)

Backend

BERT

Business Intelligence (BI)

C

Computer Vision

Computer Vision

Convolutional Neural Networks (CNN)

Convolutional Neural Networks (CNN)

Data Analysis

Data Analytics

Data Science

Data Science

Data Scientist

Data Structures

Decision Trees

Deep Learning

Deep Learning

Education

Flask

Flask

GitHub

Gradient Boosting

Heroku

Heroku

Hypertext Transfer Protocol (HTTP)

Image Processing

Image Processing

Java

k-means clustering

Keras

Keras

LightGBM

Logistic Regression

Logistic Regression

Long Short-term Memory (LSTM)

Machine Learning

Machine Learning (ML)

Mathematics

Matlab

matlab

Matplotlib

Microsoft Excel

Microsoft Office

Microsoft PowerPoint

Microsoft Word

MySQL

Natural Language Processing (NLP)

Natural Language Processing (NLP)

Neural Networks

NLTK

NLTK

NumPy

NumPy

Object detection

OpenCV

OpenCV

optimization

Pandas

Pandas (Software)

Probability

Python

Python

Python

PyTorch

Pytorch

R

R

Random Forest

Random Forest

Recommender Systems

Recurrent Neural Networks (RNN)

Recurrent Neural Networks (RNN)

Research Scientist

ResNet

RNN

Scikit

Scikit-Learn

Scikit-Learn

SciPy

scipy

Seaborn

Search

Selenium

Software Engineer

SQL

SQL

Statistics

Supervised Learning

Support Vector Machine (SVM)

Support Vector Machine (SVM)

SVM

TensorFlow

Tensorflow

test

Unsupervised Learning

Vision

XGBoost

XGBoost

Education

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    2015 - 2019

    bml munjal university

    Bachelor of Technology - BTech

    Mechanical Engineering

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    2012 - 2014

    lucknow public school

    Senior Secondary (XII)

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    2010 - 2012

    saraswati vidhya mandir

    High School (X)

Colleagues at matrixcare

Aakash Sharma

Software Engineer

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Bob Bieger

Director of Software Engineering

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Others named Aditya Vikram

Aditya Vikram Singh

Software Engineer

 at matrixcare

Aditya Vikram Dandapat

Msc Data Science

 at matrixcare

Aditya Vikram Jain

Staff Software Engineer

 at matrixcare

Aditya Vikram Singh

Senior Machine Learning Engineer

 at matrixcare

Aditya Vikram Monga

Senior Software Engineer

 at matrixcare

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Colleagues at bytelearn

Aman Tayal

Machine Learning Intern

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Amit Kumar

Software Engineer Intern

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Eish Kumar

Software Engineer

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Colleagues at paralleldots

Abdul Hameed

Frontend Engineer

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Aman Prateek

Full Stack Developer

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Aman Arora

Senior Frontend Developer

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anum anand

quality assurance engineer

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