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A list of paper, books and sites for various different topics related to machine learning and deep learning along with various field in which it is implemented

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Basics of machine learning and deep learning and its application in various fields.

  1. True understanding is making all parts of a concept so clear and vivid as if they are objects in front of you that you can manipulate as you wish.
  2. This repository contains a list various tasks that can be achieved with Machine Learning/Deep Learning.
  3. It doesn't contain any benchmark paper because I love in doing new things rather than improving previous research.

Pull Requests are welcome to add any new blog, paper, site link.

Theory:

Scikit Learn is a wonderful library for implementing basic machine learning tasks.

Naive Bayes:
  • Basics of naive bayes with term frequency and inverse document frequecy intuition [site]

Deep Learning:

Text Embedding:

Applications:

Keyword Spotting system / Wake-word detection

  • Small-footprint keyword spotting using deep neural networks [paper]
  • Convolutional Neural Networks for Small-footprint Keyword Spotting [paper]
  • A hidden Markov model based keyword recognition system [paper]

Voice activity detection

  • A simple but effective real-time voice activity detection algorithm [paper]
  • Recurrent neural networks for voice activity detection [paper]

Speech recognition and acoustic modeling

  • Training LVCSR systems on thousands of hours of data [paper]
  • Applying CNN on hybrid NN-HMM model for speech recognition [paper]
  • Convolutional Neural Networks for Speech Recognition [paper]
  • Long Short-Term Memory Recurrent Neural Network Architectures for Large Scale Acoustic Modeling [paper]
  • Understanding how deep beleif networks perform acoustic modelling [paper]

Activity Detection

  • Identifying Types of Physical Activity With a Single Accelerometer: Evaluating Laboratory-trained Algorithms in Daily Life [paper]
  • A Study on Human Activity Recognition Using Accelerometer Data from Smartphones [paper]
  • A Practical Approach to Recognizing Physical Activities [paper]

Face-recognition using FPGA

  • A self-configurable systolic architecture for face recognition system based on principal component neural network [paper]

Text Classification

  • Support Vector Machines and Word2vec for Text Classification with Semantic Features [paper]

Time Series Analysis

  • An Introductory Study on Time Series Modeling and Forecasting [paper]

Retinal vessel segmentation

  • Retinal Vessel Segmentation Using Deep Neural Networks [paper]
  • Segmenting Retinal Blood Vessels With Deep Neural Networks [paper] [implementation]
  • Retinal Vessel Segmentation Using the 2-D Gabor Wavelet and Supervised Classification[paper]

Text to Image Generation

  • Text to image Synthesis using GANs [paper] [implementation]
  • StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks [paper] [implementation]
  • StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks [paper] [implementation]
  • AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks [paper]

Object Classification and Recognition


Neural Talk 2


Neural VQA


Genre Classification

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A list of paper, books and sites for various different topics related to machine learning and deep learning along with various field in which it is implemented

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