{"metadata": {"kernelspec": {"display_name": "Python 3", "name": "python3", "language": "python"}, "language_info": {"mimetype": "text/x-python", "version": "3.6.4", "name": "python", "pygments_lexer": "ipython3", "file_extension": ".py", "nbconvert_exporter": "python", "codemirror_mode": {"name": "ipython", "version": 3}}}, "nbformat": 4, "nbformat_minor": 1, "cells": [{"cell_type": "markdown", "metadata": {"_cell_guid": "10303258-1425-4432-8399-74cfe89679eb", "_uuid": "21221c89befd1d078f5e4543a5b5e5e6f26de284"}, "source": ["I have implemented Most of the statement of the art models for this competition with fine-tuning+ dropout in the kereas \n", "This is the link of  my **github** address.\n", "\n", "[https://github.com/Ayanzadeh93/Kaggle-dog-breeds-identification](http://)\n", "\n", "i can not write code because i can not add pretrained file here. "]}, {"cell_type": "code", "metadata": {"collapsed": true, "_cell_guid": "9426dca7-0153-42cf-b139-dcda95ffad19", "_uuid": "420327a2114b3c37c84254409778766517c05945"}, "outputs": [], "execution_count": null, "source": ["# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load in \n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "# Input data files are available in the \"../input/\" directory.\n", "# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n", "\n", "from subprocess import check_output\n", "print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n", "\n", "# Any results you write to the current directory are saved as output."]}, {"cell_type": "code", "metadata": {"collapsed": true, "_cell_guid": "47bcb385-6dbb-4035-b154-c24864ebe946", "_uuid": "caa6970b185b7e58b08dea8f682faca218006520"}, "outputs": [], "execution_count": null, "source": []}]}