artem-oppermann/Sentiment-Analysis-of-Netflix-Reviews artem-oppermann/Sentiment-Analysis-of-Netflix-Reviews

  • Stars
    star
    52
  • Rank 558,916 (Top 12 %)
  • Language
    Python
  • Created over 6 years ago
  • Updated over 5 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
artem-oppermann/Sentiment-Analysis-of-Netflix-Reviews
github

artem-oppermann

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Sentiment Analysis LSTM recurrent neural network's.

More Repositories

1

Deep-Autoencoders-For-Collaborative-Filtering

Using Deep Autoencoders for predictions of movie ratings.
Python
112
star
2

Restricted-Boltzmann-Machine

Restricted Boltzmann Machine for collaborative filtering of movies.
Python
41
star
3

Deep-Reinforcement-Learning

A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
Python
36
star
4

Anomaly-Detection-in-TensorFlow-2.0

An Autoencoder for detection of anomalies implemented in TensorFlow 2.0
5
star
5

Binary-image-classification-with-CNN-s

Convolutional neural network with a custom architecture used for binary classification of images
Python
4
star
6

DCGAN

Deep convolutional generative adversarial network for image generation.
Python
1
star
7

Building-a-Real-Time-Cybersecurity-Solution

Python
1
star
8

SSD-Single-Shot-MultiBox-Detector

Object detection and classification with Single-Shot-Multibox-Detector
Python
1
star
9

Creditcard-Fraud-Prediction-with-Artificial-Neural-Networks

An artifical neural network that can identify creditcard fraud. The network is trained on the dataset that contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in two days, where there are 492 frauds out of 284,807 transactions.
Python
1
star