Publications

Recognizing low quality vehicle license plates using image based sequence recognition

  • S. Pal and P. P. Shete 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kanpur, India
  • IEEE Xplore Library Link

Projects

Interview Management System

  • Developed a web based application using Spring Boot with features of posting jobs, applying to job, scheduling interviews, and sending automatic emails wherever required.
  • Tools: Java, Spring Boot, PostGreSQL, Jpa, Thymeleaf.

OSM Route Planner (OpenStreetMap)

  • Built a Route planner in CPP that plots a path between two Cities on a map using A* Search Algorithm.
  • Used Real Map Data (OSM XML file) from the OpenStreetMap Project.
  • GitHub Link
  • Tools: C++, Graph Algorithms

IMAGE SUPER RESOLUTION

  • Designed a CNN based model which reconstructs high resolution images from the low resolution images.
  • Created a three layer model comprising of Feature Extraction, Multidimensional Mapping and Image Reconstruction phase.
  • Used T91, Set5, Set15 and Real life image dataset for performance evaluation.
  • Tools: Python, Deep Learning, OpenCV

Neural Machine Translation with Attention

  • Translated Human-Readable dates into Machine-Readable dates.
  • Implemented One of The Most Sophisticated Sequence to Sequence Attention Model.
  • Tools: Python, Deep Learning

Digital Data Encoder

  • Encoded Binary Data into Digital Signals.
  • Implemented Line coding (NRZ-L, NRZ-I, Manchester, Differential Manchester, AMI) encoder and scrambler (B8ZS, HDB3) with Random digital data generator.
  • GitHub Project Link
  • Tools: Python

TEXT EDITOR

  • Designed Text Editor using Two Stack Model.
  • Tools: C++

Certification/ Online Courses

Deep Learning Specialization: deeplearning.ai

The Deep Learning Specialization is taught by Dr. Andrew Ng, a global leader in AI and co-founder of Coursera. It Comprises of Following Five Courses.

  1. Neural Networks and Deep Learning.
  2. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.
  3. Structuring Machine Learning Projects.
  4. Convolutional Neural Networks.
  5. Sequence Models.

Certificate Link: Click Here

IITBombayX CS101.2x: Object-Oriented Programming

Topics Included:

  1. Introduction to Object Oriented Programming
  2. Classes and Methods
  3. Polymorphism
  4. Inheritance
  5. Standard Library of C++

Certificate Link: Click Here

Deep Learning: Advanced NLP and RNNs

Natural Language Processing with Sequence-to-Sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!

Certificate Link: Click Here

Python for Data Science and Machine Learning Bootcamp: Udemy

NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow.

Certificate Link: Click Here

Machine Learning By Stanford University: Coursera

This Course Provides a Broad Introduction to Machine Learning, Data Mining, and Statistical Pattern Recognition. Topics Include:

  1. Supervised Learning (Parametric/Non-Parametric Algorithms, Support Vector Machines, Kernels, Neural Networks).
  2. Unsupervised Learning (Clustering, Dimensionality Reduction, Recommender Systems, Deep Learning).
  3. Best Practices in Machine Learning (Bias/Variance Theory; Innovation Process in Machine Learning and AI).

Certificate Link: Click Here