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βž•πŸ’“Let's build the Simplest Possible Autoencoder . β‰οΈπŸ·We'll start Simple, with a Single fully-connected Neural Layer as Encoder and as Decoder. πŸ‘¨πŸ»β€πŸ’»πŸŒŸAn Autoencoder is a type of Artificial Neural Network used to Learn Efficient Data Codings in an unsupervised mannerπŸŒ˜πŸ”‘

Home Page: https://colab.research.google.com/drive/1gdnJf1ijVUfBzD6PhsLFjeQ777L9CwQf

License: GNU General Public License v3.0

Jupyter Notebook 100.00%
autoencoder autoencoder-classification autoencoder-neural-network autoencoder-model autoencoder-mnist autoencoder-clustering deep-learning deep-reinforcement-learning deep-neural-networks deep-learning-algorithms

cnn-autoencoder-deeplearning's Introduction

Deep-Learning-CNN-AutoEncoder

Makes people smile

Deep-Learning-CNN-AutoEncoder

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Business Problem

Problem Description

The goal of this project is to develop a recomendation system #DataScience for Netflix.

GitHub repo size GitHub code size in bytesGitHub top language

Few popular hashtags -

#DataScience #Netflix #Recommendation System

#Ratings #Movie PRediction #Numpy-Pandas

Motivation

About the Project

Steps involved in this project

Made with Python Made with love ForTheBadge built-with-swag

Data Overview

Libraries Used

Ipynb Ipynb Ipynb Ipynb Ipynb Ipynb Ipynb

Installation

  • Install datetime using pip command: from datetime import datetime
  • Install pandas using pip command: import pandas as pd
  • Install numpy using pip command: import numpy as np
  • Install matplotlib using pip command: import matplotlib
  • Install matplotlib.pyplot using pip command: import matplotlib.pyplot as plt
  • Install seaborn using pip command: import seaborn as sns
  • Install os using pip command: import os
  • Install scipy using pip command: from scipy import sparse
  • Install scipy.sparse using pip command: from scipy.sparse import csr_matrix
  • Install sklearn.decomposition using pip command: from sklearn.decomposition import TruncatedSVD
  • Install sklearn.metrics.pairwise using pip command: from sklearn.metrics.pairwise import cosine_similarity
  • Install random using pip command: import random

How to run?

Ipynb

Project Reports

report

Useful Links

IPYNB GitHub top language

Report - A Detailed Report on the Analysis

Contributing

PRs Welcome GitHub issues GitHub pull requests GitHub commit activity

  • Clone this repository:
git clone https://github.com/iamsivab/Deep-Learning-CNN-AutoEncoder.git

Need help?

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πŸ“§ Feel free to contact me @ [email protected]

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License

MIT Β© Sivasubramanian

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cnn-autoencoder-deeplearning's People

Contributors

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