Photo by Bekky Bekks on Unsplash

For better understanding, this post is divided into three parts:

Part 1: GAN, Autoencoders: UpSampling2D and Conv2DTranspose

In this part, introductory part and I will discuss some basic terms and processes used in this tutorial. This will help us to get the concept and better understand the other parts of this tutorial.

Part 2: Denoising image with Upsampling Layer

This part will demonstrate how we can use upsampling method for denoising an image from their input. This part will be implemented using the notMNIST dataset.

Part 3: Denoising image with Transposed Convolution Layer

This part is similar to the previous…


Photo by Bekky Bekks on Unsplash

For better understanding, this post is divided into three parts:

Part 1: GAN, Autoencoders: UpSampling2D and Conv2DTranspose

In this part, introductory part and I will discuss some basic terms and processes used in this tutorial. This will help us to get the concept and better understand the other parts of this tutorial.

Part 2: Denoising image with Upsampling Layer

This part will demonstrate how we can use upsampling method for denoising an image from their input. This part will be implemented using the notMNIST dataset.

Part 3: Denoising image with Transposed Convolution Layer

This part is similar to the previous…


Photo by Bekky Bekks on Unsplash

For better understanding, this post is divided into three parts:

Part 1: GAN, Autoencoders: UpSampling2D and Conv2DTranspose

In this part, introductory part and I will discuss some basic terms and processes used in this tutorial. This will help us to get the concept and better understand the other parts of this tutorial.

Part 2: Denoising image with Upsampling Layer

This part will demonstrate how we can use upsampling method for denoising an image from their input. This part will be implemented using the notMNIST dataset.

Part 3: Denoising image with Transposed Convolution Layer

This part is similar to the previous…


Google Colaboratory or Colab is a free Jupiter notebook environment that requires zero user configuration. It has many pre-installed ML libraries and a built-in environment to install related packages. It is one of the best available resources for using GPU and TPU without any cost.

Kaggle is also a Google subsidiary and an online community for data scientists and enthusiasts. It is often necessary to work with the Kaggle dataset in a colab notebook. Here I will discuss the easiest method to import and use the Kaggle dataset in a colab environment.

Kaggle API Setup

Kaggle API provides command-line access to the Kaggle…


We are dealing with a huge amount of data in our daily life. It adds good value if we can visualize our data and make some relation between them. Data visualization and analytic provide more control over data and give us the power to control this data efficiently.

Grafana is an open-source, feature-rich metrics dashboard, and graph editor. Grafana supports over 30 open source and commercial data sources including Graphite, Elasticsearch, OpenTSDB, Prometheus, and InfluxDB. Grafana has a plethora of visualization options to help and understand data beautifully. Another alternative of Grafana is Kabana. In this tutorial, I will discuss…

Ashrafur Rahman

Data Science Enthusiast

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