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 also. In this, article we will discuss about the datasets used to train these model and their repositories. The link of notebook for setting up the along with the article is given below:

Every year ImageNet Large scale Visual Recognition Challenge(ILSVRC) is Computer Vision competition held every year. …


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 used open source library based upon TensorFlow. It can be imported in python and any one one use it without knowing it’s internal functioning. It was released by MIT which was build on top of TensorFlow but with the release of TensorFlow 3.0 google has embedded Keras with TensorFlow officially.

Fig. 1 Keras (Source: blog.keras.io)


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 series, we will discuss state of the art model which are in public domain with code by using the APIs Keras and as well as PyTorch. The content of series content will be as follows:

Transfer Learning -Part 2

This part will be dedicated to the introduction to the Transfer Learning and environment setup…


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 from the data. This series is divided into 8 different parts which are mentioned below:

Visualization Python Libraries? Part -1

Visualization Python Libraries? Part -2

Visualization Python Libraries — Matplotlib? Part -3

Visualization Python Libraries — Seaborn? Part -4

Visualization Python Libraries — Plotly? Part -5

Visualization Libraries — GGplot? Part -6

Visualization Libraries — Bokeh? Part -7

Visualization Libraries — Pygal? Part -8

Visualization Libraries — Altair? Part -9

Hope you all have enjoyed this Visualisation Series and may be I will be able to add up to your technical skills little bit.

Need help ??? Consult with me on DDI :)


In this article will going to see how we can implement different types of graph/charts in Python using Altair Library. If you don’t have basic intuition about different types of graphs/charts/plots why they are used how they are used go through the below mentioned article to have a clear insight before implementing, It is always suggested to build a foundation strong.

For installation and enviroment setup please go through the article mentioned below:

After setting our enviroment and installing packages we can start with our implementation of various graphs using Altair with python.

  1. Structure of code

Altair has specific code…


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 becuase it is very important ti have the basic idea of how we can deploy the model. The parts of the series are mentioned below:

How to Deploy AI Models? — Part 1

Big Data Jobs

How to Deploy AI Models? — Part 2 Setting up the Github For Herolu and Streamlit

Deploy AI models -Part 3 using Flask and Json

How to Deploy AI models ? Part 4- Deploying Web-application on Heroku via Github

Trending AI Articles:

1. Why Corporate AI projects fail?

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3. Machine Learning by Using Regression Model

4…


In this article will going to see how we can implement different types of graph/charts in Python using Pygal Library. If you don't have basic intuition about different types of graphs/charts/plots why they are used how they are used go through the below mentioned article to have a clear insight before implementing, It is always suggested to build a foundation strong.

For installation and enviroment setup please go through the article mentioned below:

After setting our enviroment and installing packages we can start with our implementation of various graphs using Pygal with python.

  1. Structure of code

Pygal has specific code…


In this article will going to see how we can implement different types of graph/charts in Python using bokeh Library. If you dont have basic intituition about different types of graphs/charts/plots why they are used how they are used go throught the below mentioned article to have a clear insight before implementing, It is always suggested to build a foundation strong.

For installation and enviroment setup please go through the article mentioned below:

After setting our enviroment and installing packages we can start with our implementation of various graphs using Bokeh with python.

  1. Structure of code

Bokeh has specific code…


In this article will going to see how we can implement different types of graph/charts in R using ggplot Library. If you dont have basic intituition about different types of graphs/charts/plots why they are used how they are used go throught the below mentioned article to have a clear insight before implementing, It is always suggested to build a foundation strong.

For installation and enviroment setup please go through the article mentioned below:

After setting our enviroment and installing packages we can start with our implementation of various graphs using GGplotwith python.

  1. Structure of code

GGplot has specific code which…


In this article will going to see how we can implement different types of graph/charts in python using Plotly Library. If you dont have basic intituition about different types of graphs/charts/plots why they are used how they are used go throught the below mentioned article to have a clear insight before implementing, It is always suggested to build a foundation strong.

For installation and enviroment setup please go through the article mentioned below:

After setting our enviroment and installing packages we can start with our implementation of various graphs using Plotly with python.

  1. Structure of code

Plotly has specific code…

RAVI SHEKHAR TIWARI

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