Data science project can be a challenging but rewarding process. By following the steps we can use in this blog, you can work through the project in an organized and effective way, and ultimately arrive at a solution to your problem. Previously, we wrote blogs on many machine learning algorithms (Classification, Predication) as well as […]

# machine learning

## Mathematics Behind Support Vector Machine

Support Vector Machine is supervised machine learning algorithm. In this blog, we are going to discuss how mathematically support vector machine works. We will also discuss the types of SVM and how to implement it in Python. So, let’s get started. In the past, we’ve written articles on numerous machine learning algorithms (Classification, Prediction, and […]

## Naive Bayes From Scratch

Naive Bayes is a machine learning algorithm that is used for classification tasks. It is called "naive" because it makes a simplifying assumption about the data, specifically that the features in the data are independent of one another. Despite this assumption, the algorithm has been shown to be effective in many real-world applications. Previously, we […]

## Different Method of Model Evaluation(Part2)

Model evaluation is the process of assessing the performance of a machine learning model on a data set. It is an important step in the development of a machine learning model, as it allows us to determine how well the model is able to make accurate predictions on unseen data. Previously, we wrote blogs on […]

## Different Method of Model Evaluation(Part-1)

Accuracy is a metric that is used to evaluate the performance of a model on a classification task. It is the fraction of correct predictions made by the model on a data set, expressed as a percentage. For example, if a model makes 90 correct predictions out of 100, its accuracy is 90%. Previously, we […]

## How to do Preprocessing of Dataset Before Applying Machine Learning Algorithms

Load the dataset First, import the packages required to continue. import pandas as pd import numpy as np import matplotlib.pyplot as plt %matplotlib inline Read the dataset using Pandas Read previously loaded data and store it in a variable named df, display the first few rows with head(), by default head() will return first 5 […]

## How Mathematically Naive Bayes Classifier Works?

Previously, we wrote blogs on many machine learning algorithms as well as many other topics to help you broaden your knowledge. Please kindly visit our site and we would be glad if we got some feedback from you to improve our writing. To see some of them, you can follow the mentioned links. Linear Regression […]

## PCA From Scratch In Python

PCA is a method of dimensional reduction. When a machine learning method has a large number of features, we must choose the features that contribute the most and ignore the datasets that are less significant. This is where PCA comes into play. Consequently, PCA is an unsupervised method for choosing useful datasets from a huge […]

## News Classification with Simple Neural Network

News Classification with Simple Neural Network is one of the application of Deep Learning. And here in this part of the blog, I am going to perform a Nepali News Classification. Before jumping into the main part, I would love to share some of my previous contents based upon which this blog has been written. […]

## Stock Price Prediction On Commercial Data Using RNN

A type of neural network called a recurrent neural network (RNN) uses the output from a previous step as input for the current step. Traditional neural networks have inputs and outputs that are independent of one another, but there is a need to remember the previous words in situations where it is necessary to anticipate […]