Figure.1 Transfer Learning

In Part 4.0 of the Transfer Learning series we have discussed about VGG-16 and VGG-19 pre-trained model in depth so in this series we will implement the above mentioned pre-trained model in PyTorch. This part is going to be little long because we are going to implement VGG-16 and VGG-19…


Figure.1 Transfer Learning

In Part 4.0 of the Transfer Learning series we have discussed about VGG-16 and VGG-19 pre-trained model in depth so in this series we will implement the above mentioned pre-trained model in Keras. This part is going to be little long because we are going to implement VGG-16 and VGG-19…


In Part 3 of the Transfer Learning series we have discussed the datasets on which these pre-trained model is trained for the ILVRC competition which is held annually and their repository as well as the documentation in order to implement this concept with two API’s namely Keras and PyTorch. In…


In Part 2 of the Transfer Learning series we have discussed, we have discussed how we can set-up our environment in Jupyter Notebook which is compatible with Colab, Binder and in our Local System also. We also discussed what if Transfer Learning how we can use it with less data…


In the previous article, we discussed the layout of the Transfer Learning Series. In this article we will have a deep intuition about Transfer Learning and installation of libraries in which we will implement these concepts.

1. Library Installation

We will use two API’s which are mentioned below:

Keras: It is most widely…


In this series, we will discuss Transfer Learning. Transfer Learning was a breakthrough in Artificial Intelligence which enables several other sectors in which collecting huge datasets was a problem to employ this mechanism and fine tune the per-trained neural network on their datasets which is small in number.

(Source: Georgion.io)

In this…


This is the concluding article of the Visualisation Series using Python and R. In this series i tried to cover as much as libraries as possible. These library includes different techniques as well as different plots which help us to visualise the data as well as to get the insight…


In this article will going to see how we can implement different types of graph/charts in Python using Altair Library. …


This is the concluding article of the Model Deployment Series. In this series we saw various techniques which can be used to deployed any ML model. We also touched the upper layer of the CICD via Git and Github - version control. This series was specifically dedicated for model deployment…


In this article will going to see how we can implement different types of graph/charts in Python using Pygal Library. …

RAVI SHEKHAR TIWARI

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store