About Me

A multi-faceted, result-oriented & competent professional with nearly 2 years of comprehensive experience; targeting challenging and rewarding opportunities with an organization of repute.

• Skilled in gathering inputs from users...rtunities with an organization of repute.

  • Skilled in gathering inputs from users & leveraging given data for creating reliable algorithms that predict future behaviour

  • Competency in research & implementation of appropriate ML algorithms & AI tools

  • Proper understanding of machine learning algorithms; developed analytical methods to support novel approaches of data and information processing

  • Insightful experience in project management activities including project scoping, estimation, planning, finalization of technical / functional specifications, resource administration and quality management

  • Built end-to-end interactive machine learning models; worked in deployment of ML models related to the business needs

  • Capability in devising and implementing Statistical / Predictive Models and Machine Learning Algorithms utilizing diverse sources of data

  • Gained experience in manipulating and analysing complex, high-volume, high-dimensionality data from varying data sources

  • Supported majorly in the development of innovative business solutions to improve product performance and reduce cost by leveraging combination of domain knowledge, Data Science & Data Engineering skills

  • Helping out the community in Data Science and Deep Learning as a volunteer & speaker at Mantissa Data Science Meetup Group

  TECHNICAL SKILLS

  • Knowledge of: Algorithms, OOP, Data Structures, Regex, Statistics, debugging, Linux Commands, containers (docker), REST API, Calculus & Algebra

  • DBMS: SQL, NoSQL

  • Cloud: AWS, GCP

  • Version Control: Git

  • Coding: Python, C++, C, Octave/Matlab, Bash

  • Data-handling: Numpy, Pandas, Scikit-learn

  • Computer Vision: Object Detection & Segmentaion (OpenC, PIL)

  • NLP: Gensim, Spacy, Transformers

  • Data Visualization: Matplotlib, Plotly, seaborn

  • ML/DL Libraries: Keras, PyTorch, TensorFlow, Fastai, Caffe (ONNX, MMDNN), H20, AutoKeras

  • Data Science: Regression, Time-Series Analysis, Bayesian Methods, Tree-Based Learners, SVM, Dimensionality Reduction, Data Mining, Recommendation Systems

  • NVIDIA: TensorRT, NVDLA

  • Areas of Interest: Auto ML, Task Automation, NLP

   

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