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gsanc018 / test_classify.py
Created June 21, 2016 05:14 — forked from manacoa/test_classify.py
A quick "hello world" type classifier application for the latest version of Caffe. Draws heavily from classify.py (which doesn't print results) and the jetapac fork of this file (which prints results but isn't compatible with the latest version!).
#!/usr/bin/env python
"""
classify.py is an out-of-the-box image classifer callable from the command line.
By default it configures and runs the Caffe reference ImageNet model.
"""
import numpy as np
import os
import sys
import argparse
@gsanc018
gsanc018 / machine-learning-basics.py
Created May 30, 2016 13:21 — forked from pupadupa/machine-learning-basics.py
Some machine learning algorithm for Titanic dataset. SVM, Random Forest, XGBoost. Link to kaggle https://www.kaggle.com/c/titanic
# Be sure that you have installed libraries (if not - google it):
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import xgboost as xgb
from sklearn.preprocessing import LabelEncoder
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.metrics import mean_squared_error
from sklearn import cross_validation
@gsanc018
gsanc018 / geneticAlgorithms
Created May 22, 2016 02:31 — forked from thertrader/geneticAlgorithms
Using Genetic Algorithms in Quantitative Trading
############################################################
## Using Genetic Algorithms in Quantitative Trading
##
## thertrader@gmail.com - Mar 2014
############################################################
library(PerformanceAnalytics)
library(rgenoud)
library(quantmod)
library(TTR)