Pinned

1. Happy-or-not Public

   In this mini-experiment, I build a classifier that finds if the person(s) in a given image are happy or not.

   Jupyter Notebook

2. JIRA-Similar-Issue-Finder-App Public

   A JIRA Bot that can train a machine learning model and comment related JIRA IDs on a list of JIRA issues.

   Jupyter Notebook 14 11

3. hinglish-data-generation Public

   This is a try at generating a big dataset of hinglish, which currently does not exist

   Python

4. Headless-RaspberryPi-Twitter-Controller-Bot Public

   A simple twitter bot that runs on raspberry pi and could return its IP address and more info.

   Python

5. Caltech-101-Object-Classification Public

   Multiple approaches tried for Object classification on Caltech 101 Dataset

   Jupyter Notebook 4 4

6. Troubleshooting Convolutional Neural...

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   ### Troubleshooting Convolutional Neural Networks 

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   #### Intro

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   This is a list of hacks gathered primarily from prior experiences as well as online sources (most notably [Stanford's CS231n](http://cs231n.github.io/) course notes) on how to troubleshoot the performance of a convolutional neural network . We will focus mainly on supervised learning using deep neural networks. While this guide assumes the user is coding in Python3.6 using tensorflow (TF), it can still be helpful as a language agnostic guide.

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