Note: This post requires knowledge of Python, Deep Learning, Image preprocessing, and classification model evaluation. If you are not familiar with these concepts, please feel free to leave this post. Thank you…
Namste Everyone… In this post, we will classify the Indian food images. India is known for its multi-culturalism. This multi-culturalism also influences Indian food. We have lots of variety in our Indian food. Food varies inter-state and intra-state across India. We will apply deep learning algorithms to identify these food items. Our objective is to make you familiar with deep classification networks with catchy example. This post will…
In the previous part we have covered basic drawings in Turtle. In this post we will take forward our dicsussion. If you haven’t read the previous part, please visit the following link:
Circle: We can draw a circle of radius n with the help of cricle(n) method of Turtle class.
Namste…. everyone. In this post I will discuss an interesting python library called “Turtle”. Yes, you heard it right, “Turtle in Python”. Turtle is originally an extension of Logo programming language. Wally Feurzeig, Seymour Papert and Cynthia Solomon developed the Logo language in 1970. Current version of Turtle is 3.9.1, and 3.10 is under development. I will go through the basic functions of a turtle. I will try to provide a playground where you can make more complex and attractive pictures with the help of this library. The turtle provides you with a moving object that can draw various colorful…
Hello All, In the Machine Learning domain, model performance evaluation is a critical phase. Based on the evaluation, we take the final call to deploy our model or not. There are various metrics used by the researcher and practitioners to evaluate their models. Metrics may vary according to the nature of the problem. Example: We use Accuracy, Precision, Recall for classification models, BLEU, Meteor, and Rouge for Machine Translation models. This post will focus on classification metrics and see how the Accuracy score can mislead you. It is a well-known fact that we shouldn’t be satisfied with only Accuracy score…
Welcome you all to my new story. Here, We will discuss the Word Cloud, which is graphical representation of our Text data. We will see some practical examples using Python language. Let’s start………….
Hello all, In this post, I am going to share some interesting styling tips to make your Jupyter Notebook attractive. We will use Emojis to enrich our notebook files. Here, you will get programmatic as well as copy-paste way to use Emojis.
Jupyter notebook is an open source web application framework, which allows you to code and share your data. It has interactive output facility. Code documentation in the desired format (pdf, HTML, etc.) can be generated at the same place. For detailed information, have a look at the following post: Getting Started With Jupyter Notebook for Python
In the previous post (part 1.1), I have given you the Introduction of Django Design Patterns(DDPs). We have also discussed a few Design Patterns. Here, we will continue our journey of DDPs. We have completed Structural Design Patterns under the Model section. Now its time to discuss some more DDPs.
Data has been taken from the following Book. https://doc.lagout.org/programmation/Django/Django%20Design%20Patterns%20and%20Best%20Practices%20%5BRavindran%202015-03-26%5D.pdf
I am forwarding the idea of the above book in a summarized manner. For in-depth study follow the book.
A pattern is a kind of regularly occurring structure or repeated design. A pattern is actually a generalized solution for commonly occurring problems. We are surrounded by various kinds of patterns in different fields. One example is given below:
SymPy is the python library support for Symbolic Mathematics. https://www.sympy.org/ is the official page of SymPy. Main objective of the SymPy is to provide support for Algebric Compuation in Python language. SymPy is “free to use and very light weight library”. SymPy is fully coded in Python, hence it has same limitations as Python.
Latest version of SymPy is 1.3 (released in Sept’18). Anaconda comes with pre-installed SymPy. You can update is as follows:
$conda update sympy
SymPy has additional dependancy on mpmath, which also comes with anaconda. You can install it as follows:
$conda install mpmath
First Example of…
PhD Research Scholar CSE Dept. PDPM IIITDMJ India