All you need to know about the famous Object Detection algorithm

You may have heard your friend talking about Object Detection and perhaps utter the words like YOLO and Faster-RCNN. If you’ve wondered what YOLO meant and why you should even care about it look no further.

This blog will provide an exhaustive study of YOLOv3 (You only look once, version…


A brief Introduction

Tensorflow is a deep learning library that makes building and deploying Deep Learning Applications super easy. If you wondered what this library is all about wait no more, keep reading the blog to find what makes Tensorflow unique.

This blog provides an overview to the Tensorflow library and provides a…


Learn the why, what and how of Docker

In this blog we’ll try to understand one of the most popular tools used to containerize and deploy applications over the internet i.e. Docker. It makes deploying applications extremely simple.

We will try to look at the things that make Docker so special and learn how you can build, deploy…


A Brief Overview

Introduction

Support Vector Machines (SVMs) are a set of supervised learning methods which learn from the dataset and can be used for both regression and classification. …


and its implementation in Python

In this blog we’ll try to dig deeper into Random Forest Classification. Here we will learn about ensemble learning and will try to implement it using Python.

You can find the code over here.

Random Forest Classifier :

It is an ensemble tree-based learning algorithm. The Random Forest Classifier is a set of decision…


Getting started with Logistic Regression theory

Introduction

Logistic Regression is a Supervised learning algorithm widely used for classification. It is used to predict a binary outcome (1/ 0, Yes/ No, True/ False) given a set of independent variables. To represent binary/ categorical outcome, we use dummy variables.

Logistic regression uses an equation as the representation, very much…


An introduction to Decision Tree Classifier

A Decision Tree is a simple representation for classifying examples. It is a Supervised Machine Learning where the data is continuously split according to a certain parameter.

Decision Tree consists of :

  1. Nodes : Test for the value of a certain attribute.
  2. Edges/ Branch : Correspond to the outcome of a test and connect to…


A Brief Introduction

In this blog, we’ll talk about one of the most widely used machine learning algorithms for classification, which is the K-Nearest Neighbors (KNN) algorithm. …


Along with its implementation in Python

In this blog we’ll try to understand one of the most important algorithms in machine learning i.e. Random Forest Algorithm. We will try to look at the things that make Random Forest so special and will try to implement it on a real life dataset.

The Code along with the…


A step by step Approach

We’re going to be implementing Linear Regression on the ‘Boston Housing’ dataset.

The Boston data set contains information about the different houses in Boston. There are 506 samples and 13 feature variables in this dataset. …

Afroz Chakure

Programmer | Blogger | Linkedin : linkedin.com/in/afroz-chakure-489780168

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