Pradip Dharam's Projects
Amazon Fine Food Reviews is a classic Sentiment Analysis problem used to classify the polarity of the review given by the Amazon user. Given the textual reviews and related features of the product, I have designed various techniques to classify the polarity of the review.
ATM Machine Low Level Design. Sate Design Pattern is been used to define finite states classes for defined abstraction.
Convolutional Neural Networks (CNN) in Computer Vision in Deep Dearning under the umbrella of Artificial Intelligence is been used to classify 20 Newsgroups documents.
Recurrent Neural Network called LSTM (Long Short Term Memory) is been used to engineer the features for the funding proposal text features, it learns the sequence of words. This is to reduce the efforts for DonorsChoose.org to reduce down the effors in filtering the proposals for approvals.
Designing an E-commerce Application. Handling payments, permissions, sercher etc are introduced. Add products functionalities are incorporated using command design pattern. Cart & Order manager are designed.
Enquiry Handler's Low Level Design. Equiry is passed to the chain. Whatever node it matches the enquiry, the log handler logs the enquiry type. It demostrates the maninly Chain of Responsibility Design Patten along with Factory Design Pattern.
Find optimal k and accuracy
Observations on Haberman's Cancer Survival data set
Spectrogram created using librosa library are feeded to Recurrent Neural Network called LSTM (Long Short Term Memory) is been used to engineer the features for voice data set, to achieve the classification of spoken digits. RNN or Recurrent Neural Networks in Deep Learning or Artificial Intelligence is the foundational baseline for NLP.
Sports Scoreboard Push Notification Design. Push notification from the respective publisher to all its respective subscribers is sent. Observer design pattern plays an important role here.
Stochastic Gradient Descent for Linear regression MANUAL implementation
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent