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@joncardasis
joncardasis / Storing-Images-On-Github.md
Last active February 2, 2024 02:30
Storing Images and Demos in your Repo

Storing Images and Demos in your Repo

In this quick walkthough you'll learn how to create a separate branch in your repo to house your screenshots and demo gifs for use in your master's readme.

How to

1. Clone a fresh copy of your repo

In order to prevent any loss of work it is best to clone the repo in a separate location to complete this task.

2. Create a new branch

Create a new branch in your repo by using git checkout --orphan assets

@pandafulmanda
pandafulmanda / Python3 Virtualenv Setup.md
Last active March 12, 2024 15:59 — forked from akszydelko/Python3 Virtualenv Setup.md
Setting up and using Python3 Virtualenv on Mac

Python3 Virtualenv Setup

Requirements
  • Python 3
  • Pip 3
$ brew install python3
@fchollet
fchollet / classifier_from_little_data_script_2.py
Last active September 13, 2023 03:34
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@fchollet
fchollet / classifier_from_little_data_script_1.py
Last active November 28, 2023 07:12
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@briandk
briandk / CONTRIBUTING.md
Created March 18, 2016 20:29
A basic template for contributing guidelines that I adapted from Facebook's open source guidelines

Contributing to Transcriptase

We love your input! We want to make contributing to this project as easy and transparent as possible, whether it's:

  • Reporting a bug
  • Discussing the current state of the code
  • Submitting a fix
  • Proposing new features
  • Becoming a maintainer

We Develop with Github

@lukas-h
lukas-h / license-badges.md
Last active May 1, 2024 10:20
Markdown License Badges for your Project

Markdown License badges

Collection of License badges for your Project's README file.
This list includes the most common open source and open data licenses.
Easily copy and paste the code under the badges into your Markdown files.

Notes

  • The badges do not fully replace the license informations for your projects, they are only emblems for the README, that the user can see the License at first glance.

Translations: (No guarantee that the translations are up-to-date)

@vasanthk
vasanthk / System Design.md
Last active May 4, 2024 16:39
System Design Cheatsheet

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

  1. Clarify and agree on the scope of the system
  • User cases (description of sequences of events that, taken together, lead to a system doing something useful)
    • Who is going to use it?
    • How are they going to use it?
@toboqus
toboqus / btree.cpp
Created November 3, 2015 08:53
Binary tree implementation in c++
#include <iostream>
using namespace std;
struct node{
int value;
node *left;
node *right;
};
@baraldilorenzo
baraldilorenzo / readme.md
Last active November 21, 2023 22:41
VGG-16 pre-trained model for Keras

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

@karpathy
karpathy / min-char-rnn.py
Last active May 4, 2024 17:44
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)