Install Tensorflow

Tensorflow is a library/platform created by and open-sourced by Google. It is the most used library for deep learning applications. Now, creating a neural network might not be the primary function of the TensorFlow library but it is used quite frequently for this purpose. So before going ahead let’s install and import the TensorFlow module.

Using the pip/conda command to install TensorFlow in your system

# terminal/zsh/cmd command
# pip
pip install tensorflow --upgrade

# conda
conda install -c conda-forge tensorflow
%tensorflow_version 2.x

Implementing Neural Networks Using TensorFlow

Deep learning has been on the rise in this decade and its applications are so wide-ranging and amazing that it’s almost hard to believe that it’s been only a few years in its advancements. And at the core of deep learning lies a basic “unit” that governs its architecture, yes, It’s neural networks.

A neural network architecture comprises a number of neurons or activation units as we call them, and this circuit of units serves their function of finding underlying relationships in data. And it’s mathematically proven that neural networks can find any kind of relation/function regardless of its complexity, provided it is deep/optimized enough, that is how much potential it has.

Now let’s learn to implement a neural network using TensorFlow

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Install Tensorflow

Tensorflow is a library/platform created by and open-sourced by Google. It is the most used library for deep learning applications. Now, creating a neural network might not be the primary function of the TensorFlow library but it is used quite frequently for this purpose. So before going ahead let’s install and import the TensorFlow module....

Download and Read the Data

You can use any dataset you want, here I have used the red-wine quality dataset from Kaggle. This is a classification problem, of course, you can learn to apply the concept to other problems. First, download the dataset in your working directory. Now that the data is downloaded let’s load the data as data frame....

Data Preprocessing/ Splitting into Train/Valid/Test Set

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Create Model Neural Network

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Training The Model

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Generate Predictions and Analyze Accuracy

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