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Machine Learning | Deep Learning | Data Science | Web Dev
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  1. Sequential

Probability Distribution Thumbnail

What is a Probability Distribution ?

What are Convolutional Neural Networks ?

About the Dataset


Let’s jump to the code part :

1. Importing The Dataset

#importing the libraries import numpy as np import tensorflow as tf import pandas as pd import matplotlib.pyplot…

What is Linear Regression ?


#normal distribution
x1 = tf.random.normal(shape=(5,5),mean=0,stddev=1)
#normal distribution
output: tf.Tensor( [[-1.1473149e+00 5.1616412e-01 -2.8656033e-01 -1.4161720e-03 -6.7782238e-02] [ 1.5549400e-01 -1.8609362e+00 7.8299832e-01 -7.3712116e-01 -3.0330741e-01] [ 5.6524660e-02 1.0138390e-01 1.2218195e+00 1.2505690e+00 3.0457941e-01] [ 3.6436683e-01 -8.6699528e-01 1.5152076e+00 7.8330201e-01 -1.4127023e+00] [-1.2999429e+00 1.3505920e+00 1.0376108e+00 -1.5029492e+00 9.7778231e-01]]…

What is Tensorlfow ?

Advantages of Tensorflow 2 over The first Version


Tensor Basics


What are RNNs and LSTMs ?

What is Sentiment Analysis ?

Jumping to Code

  1. Importing the Libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import nltk
df = pd.read_csv('IMDB Dataset.csv')

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