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Zafarali Ahmed zafarali

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@Ashioto
Ashioto / ActorCritic.py
Last active June 20, 2019 09:29
Solution to Continuous MountainCar problem
import tensorflow as tf
import numpy as np
import os
import gym
import time
import sklearn
import itertools
import sklearn.pipeline
import sklearn.preprocessing
from sklearn.kernel_approximation import RBFSampler
@soply
soply / disp_multiple_images.py
Last active January 9, 2024 14:52
Plot multiple images with matplotlib in a single figure. Titles can be given optionally as second argument.
import matplotlib.pyplot as plt
import numpy as np
def show_images(images, cols = 1, titles = None):
"""Display a list of images in a single figure with matplotlib.
Parameters
---------
images: List of np.arrays compatible with plt.imshow.
@EderSantana
EderSantana / CATCH_Keras_RL.md
Last active October 16, 2023 08:32
Keras plays catch - a single file Reinforcement Learning example
@alexgorban
alexgorban / tf_scopes.py
Created March 11, 2016 04:52
"""Illustration for various types of namespace scopes in TensorFlow.
> python tf_scopes.py
foo_name_scoped :
v.name= v:0
v2.name= foo_name_scoped/v2:0
a.name= Variable:0
b.name= Variable_1:0
result_op.name= foo_name_scoped/Add:0
foo_op_scoped :
@karpathy
karpathy / min-char-rnn.py
Last active May 30, 2024 23:33
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)
@bonzanini
bonzanini / sentiment_classification.py
Last active October 30, 2020 23:58
Sentiment analysis with scikit-learn
# You need to install scikit-learn:
# sudo pip install scikit-learn
#
# Dataset: Polarity dataset v2.0
# http://www.cs.cornell.edu/people/pabo/movie-review-data/
#
# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/19/sentiment-analysis-with-python-and-scikit-learn
@tonymtz
tonymtz / gist:d75101d9bdf764c890ef
Last active May 7, 2024 13:07
Uninstall nodejs from OSX Yosemite
# first:
lsbom -f -l -s -pf /var/db/receipts/org.nodejs.pkg.bom | while read f; do sudo rm /usr/local/${f}; done
sudo rm -rf /usr/local/lib/node /usr/local/lib/node_modules /var/db/receipts/org.nodejs.*
# To recap, the best way (I've found) to completely uninstall node + npm is to do the following:
# go to /usr/local/lib and delete any node and node_modules
cd /usr/local/lib
sudo rm -rf node*
@jakevdp
jakevdp / CategoricalCMAP.ipynb
Last active February 14, 2024 18:00
Example of a categorical color map in matplotlib
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@jakevdp
jakevdp / discrete_cmap.py
Last active May 29, 2024 18:50
Small utility to create a discrete matplotlib colormap
# By Jake VanderPlas
# License: BSD-style
import matplotlib.pyplot as plt
import numpy as np
def discrete_cmap(N, base_cmap=None):
"""Create an N-bin discrete colormap from the specified input map"""
@erichurst
erichurst / US Zip Codes from 2013 Government Data
Created December 9, 2013 23:00
All US zip codes with their corresponding latitude and longitude coordinates. Comma delimited for your database goodness. Source: http://www.census.gov/geo/maps-data/data/gazetteer.html
This file has been truncated, but you can view the full file.
ZIP,LAT,LNG
00601,18.180555, -66.749961
00602,18.361945, -67.175597
00603,18.455183, -67.119887
00606,18.158345, -66.932911
00610,18.295366, -67.125135
00612,18.402253, -66.711397
00616,18.420412, -66.671979
00617,18.445147, -66.559696
00622,17.991245, -67.153993