A little motivation ..! Watch it guys ☺

Monthly Post — 01

Hi! First of all, I wish you all that this year will bring new happiness, new goals, new achievements, and a lot of new inspirations in your life. Wishing you a year fully loaded with happiness. The new year arrived so it's time to note down a new resolution. My plan for this year is to learn more concepts on Machine learning, Cloud computing, and Improve my programming skills. Before that, I thought of writing blogs regularly whatever the new concepts I came across on the internet, and learning through my…

Photo by Raul Varzar on Unsplash

This is my continuation blog, please if you did not read the previous blog kindly request all to refer before this.

Hi to all! I hope all are safe! Let’s delve into the concept.

Topics Covered

01. Pasting vs. bagging

02. Random forests as ensembles of decision trees

03. Random patches

04. Random subspaces

05. Build more random, diverse individual predictors using Extra Trees

Here we will confer about how averaging methods can be used to build ensemble models. Averaging involves training multiple predictors in parallel, and these predictors train on random subsets of our training data. Pasting is similar…


Even as the number of machine learning frameworks and libraries introduced on a daily basis scikit-learn is retaining its popularity with ease. In particular, scikit-learn features extremely comprehensive support for ensemble learning, which is an important technique to mitigate overfitting. Ensemble learning is one of the most fascinating concepts in ML. I will discuss the development process of several important types of ensemble learning models.

Table of Contents

01) Decision trees and random forests — Ideal blocks for ensemble learning

02) Averaging and boosting techniques

03) Bagging and pasting

04) Constructing boosting models

05) Utilizing model stacking

Throughout this blog I’ll discuss how…

Hi to all, In this blog, I am gonna to discuss the NLP concepts using TensorFlow. I am writing this blog with the help of TensorFlow in the Practice Session course in Coursera. It’s one of the best courses for the beginners to get to know about TensorFlow.


For this, we should have a haar cascade_fullbody.xml file and the video footage which is taken from a CCTV camera.

Initially, we will be importing the various packages which are required, so we require computer vision, we require numerical python also we require time

We used cv2.CascadeClassifier is a built-in function and we give the path of the file, the.XML file. …

Scikit-learn the most used machine learning library in Python. It has lots of inbuilt API and tools relates to machine learning algorithms. But its support for the neural network is very limited.

Pytorch is an open-source deep-learning library like TensorFlow and Keras it helps hugely in building neural networks. It’s known for providing the most high-level features such as tensor computations with strong GPU acceleration support and building deep neural networks on a tape-based autograd systems. Developed by facebook’s AI group.

for better understand about Pytorch refer below link.

Skorch is the union of Scikit-learn and Pytorch. Simply we can…

Routing types and Routing Protocols

Communication is incredibly important in today’s technological world. And much of these communications is happens through a very complex web of networks throughout the world. Taking information from one point to another point is called networking. So it’s very important to have the knowledge of routing process and the types of routing protocols we need to use. Routing makes the internet possible.

To begin to start about Routing Technologies we have to know about what is routing? and what taking place when a router routes a packet? We can simply define routing is the process…

Hi, I’m Vidush! Welcome to my first blog post!

In this article, I will discuss basic image processing using python. A lot of applications and fields are using images so with this there is usually a need to process the images used. In python, there are a lot of libraries you could use to do image processing such as OpenCV, scikit-image, Python Imaging Library, and Pillow. In this article, we will focus on using open cv.

These are the basic image processing operations Load Display Save images, Scaling, Flipping, Varying Brightness, Bitwise operations, Blurring and Sharpening, Thresholding, Erosion and Dilation…

Vidushraj Chandrasekaran

Fresh Graduate in Electrical & Telecommunication Engineering | Machine Learning and Deep Learning Enthusiast

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