Avishek Mukherjee's Projects
This repo contains the code solutions for https://www.byte-by-byte.com/6-weeks-sp
Using Python wrappers, practicing, Udacity exercises
Autoencoder model for rare event classification
A collection of important graph embedding, classification and representation learning papers with implementations.
A collaborative list of awesome UI & Animation only in Swift. Quick preview.
A curated list of awesome mathematics resources
A curated list of object proposals resources for object detection
A topic-centric list of HQ open datasets. PR ☛☛☛
A curated list of awesome READMEs
A list of awesome Robotics resources
A curated list of awesome scientific Python resources
TensorFlow - A curated list of dedicated resources http://tensorflow.org
This is a backup of the codes and tutorials on my machine
All the courses that I did on Bayesian Statistics and its nuances, and some of the work books.
Mapping a variable-length sentence to a fixed-length vector using BERT model
Question Answering after fine tuning Distil-BERT.
Coding interview questions and solutions
Weakly Supervised Learning for Findings Detection in Medical Images
Experiments with MovieLens Database to build a Collaborative Filtering Model
This is my try at building a single view iOS app that changes color at the click of a button.
An elementary but bad attempt by me to implement Concurreny Control in Java based on Timestamp-based Concurrency, Thomas Write Rule, Strict 2 phase locking using Reentrant Read Write Locks implemented in the class of Prof. Jeong Hwang
Sentiment Classification of Corona Tweets using sequence classification
fast.ai Courses
Constructed a DenseNet121 for Medical Image Analysis based on the paper Densely Connected Convolutional Networks, by Gao Huang et al, Backend used is Tensorflow Keras.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
A DFS implemented on a Swift Playground
A collection of Dynamic Programming problems solved on LeetCode
Generating Word Embeddings based on the Word2Vec model of (Mikolov et al.) and making their TSNE projections using PLOTLY Data Visualization library. Text obtained from NLTK GutenBerg. Libraries used: NLTK, GENSIM, SKLEARN, PICKLE (For data serialization -- storing the Word2Vec model)
Deep Neural Networks Based Approaches for Graph Embeddings
Database Programming Assignment under Prof. Jeong Hyon Hwang.