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View Kmeans.py
import pandas as pd
import numpy as np
#create a dummy data
user_id = [x for x in range(10000)]
recency = np.random.randint(low=1, high=10, size=10000)
monetary = np.random.randint(low=1, high=10, size=10000)
frequency = np.random.randint(low=1, high=10, size=10000)
View resnet50.py
import tensorflow as tf
import os
from tensorflow.python.keras.applications import ResNet50
from tensorflow.python.keras.models import Sequential
from tensorflow.python.keras.layers import Dense, Flatten, GlobalAveragePooling2D
from tensorflow.python.keras.applications.resnet50 import preprocess_input
from tensorflow.python.keras.preprocessing.image import ImageDataGenerator
@Madhivarman
Madhivarman / learntomake5.py
Created May 10, 2018
Using Reinforcement Learning - QTable Algorithm algorithms learns to make 5 within three attempts. Input number ranges from 1 to 12.
View learntomake5.py
import random
import numpy as np
class Game:
def __init__(self):
self.reset()
def reset(self):
self.current_number = random.randrange(1,12)
@Madhivarman
Madhivarman / pong.py
Created May 8, 2018
A Neural Network model that learns to play a PONG game from the image RAW pixels.
View pong.py
import gym
import numpy as np
env = gym.make("Pong-v0")
observation = env.reset()
#hyperparameters
episode_number = 0
batch_size=10 #how many episodes to wait before moving the weights
gamma = 0.99 #discount factor for reward
@Madhivarman
Madhivarman / model_demo.py
Last active Jun 6, 2019
TensorFlow Code - Training a model to count how many ones are there in the string.
View model_demo.py
#train model to count number of 1's present in the string
import numpy as np
from random import shuffle
#import necessary libarary
import tensorflow as tf
training_data = ['{0:020b}'.format(i) for i in range(2**20)]
shuffle(training_data)
train_input = [map(int,i) for i in training_data]
ti = [] #list to store each tensor
View text_segment.py
"""Sentence segmentation, means, to split a given paragraph of text into sentences, by identifying the sentence boundaries.
In many cases, a full stop is all that is required to identify the end of a sentence, but the task is not all that simple.
This is an open ended challenge to which there are no perfect solutions. Try to break up given paragraphs into text into
individual sentences. Even if you don't manage to segment the text perfectly, the more sentences you identify and display
correctly, the more you will score."""
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
View DFS.py
from collections import defaultdict
class Graph():
#initial declaration
def __init__(self):
self.graph = defaultdict(list)
#add edge between two vertices
def addedge(self,src,dist):
View linkedlist.py
class Node:
#creation of node
def __init__(self,data):
self.data = data #assign data
self.next = None #initialize null
class LinkedList:
@Madhivarman
Madhivarman / SprialMatrix.java
Last active Sep 9, 2017
Spiral Matrix logic implemented in java
View SprialMatrix.java
//spiral matrix method is used
import java.io.*;
import java.util.Scanner;
public class BrainTeaser{
static int[] array = new int[200];
static int userchoice;
//brainFunction called here
@Madhivarman
Madhivarman / Bruteforce.java
Last active Oct 6, 2019
String Pattern matching using BruteForce Algorithm
View Bruteforce.java
//brute force algorithm
//string matching
import java.io.*;
import java.util.Scanner;
class Bruteforce{
//called function
public static int bruteforce(String text,String tobematched){
int length = text.length();//length of the text
int plength = tobematched.length();//length of the pattern;
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