Jeremiah Kamama JeremiahKamama

## keybase.md

      
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                JeremiahKamama
                / keybase.md
            
            
              Created
              August 16, 2021 07:56
            
          
    Keybase proof

I hereby claim:

I am jeremiahkamama on github.
I am jeremiahkamama (https://keybase.io/jeremiahkamama) on keybase.
I have a public key ASBcKBTtk6IzaBWZutoqPQv4ShnQP57MOHeE8I4Bw4I5fAo

To claim this, I am signing this object:

  
## sample.py
text = "Our private lives have become a public commodity. Today, the business model of the web is to provide free services in exchange for personal data. Web services then sell this data. The user is not given a choice and is instead forced to give up their data in exchange for the services they want, and often in exchange for nothing, at the cost of personal privacy."
print(text)

doc = nlp(text)


words = [word.text for word in doc]
print(words)

## train.py
history = model.fit(train_pad, y_train, validation_split=0.3, epochs=5, batch_size=1000, shuffle=True, verbose = 1)

## tokenizer.py
tokenizer = Tokenizer(num_words= 15000)
tokenizer.fit_on_texts(review)

## text_to_sentence.py
train_tokens = tokenizer.texts_to_sequences(X_train)
test_tokens = tokenizer.texts_to_sequences(X_test)

## summary.py
model.summary()

## split.py
X = imdb['review']
y = imdb['sentiment']

X_train,X_test, y_train,y_test = train_test_split(X,y, test_size=0.2, random_state=42)

## replace.py
imdb.sentiment.replace("positive", 1 , inplace= True)
imdb.sentiment.replace("negative", 0, inplace= True)
imdb.head()

## readcsv.py
imdb = pd.read_csv('/content/drive/MyDrive/data/IMDB.csv')

imdb.head()

## poscloud.py
plt.figure(figsize = (20,20))
cloud = WordCloud(max_words= 2000, width= 1600,height= 800).generate("".join(imdb[imdb.sentiment == 1].review))
plt.imshow(cloud, interpolation='bilinear')
	text = "Our private lives have become a public commodity. Today, the business model of the web is to provide free services in exchange for personal data. Web services then sell this data. The user is not given a choice and is instead forced to give up their data in exchange for the services they want, and often in exchange for nothing, at the cost of personal privacy."
	print(text)

	doc = nlp(text)


	words = [word.text for word in doc]
	print(words)
	tokenizer = Tokenizer(num_words= 15000)
	tokenizer.fit_on_texts(review)
	train_tokens = tokenizer.texts_to_sequences(X_train)
	test_tokens = tokenizer.texts_to_sequences(X_test)
	X = imdb['review']
	y = imdb['sentiment']

	X_train,X_test, y_train,y_test = train_test_split(X,y, test_size=0.2, random_state=42)
	imdb.sentiment.replace("positive", 1 , inplace= True)
	imdb.sentiment.replace("negative", 0, inplace= True)
	imdb.head()
	imdb = pd.read_csv('/content/drive/MyDrive/data/IMDB.csv')

	imdb.head()
	plt.figure(figsize = (20,20))
	cloud = WordCloud(max_words= 2000, width= 1600,height= 800).generate("".join(imdb[imdb.sentiment == 1].review))
	plt.imshow(cloud, interpolation='bilinear')