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

## Text Analysis with WordCloud in Python

WordCloud in Python can be done in different ways but one of the most popular and easier ones is using the package wordcloud. We can install it using the following way. !pip install wordcloud Requirement already satisfied: wordcloud in c:\programdata\anaconda3\lib\site-packages (1.8.1) Requirement already satisfied: pillow in c:\programdata\anaconda3\lib\site-packages (from wordcloud) (8.0.1) Requirement already satisfied: numpy>=1.6.1 in […]

## 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 have authored blog posts covering a wide range of topics, […]

## WorldCup Tweet Sentiment Analysis in Python

WorldCup tweet sentiment analysis will be done based on tweets related to the world cup. This is a time of the world cup and social media might be full of activities related to the world cup. Most of us pick a side with the country and make posts based on them or against other teams. […]

## 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 […]

## Auto-encoders from Scratch in Python

Auto-encoders from scratch will be done over the concept of Neural Network from Scratch that I already did. You can find it on my following blogs. Feed Forward Neural Network from Scratch Convolutional Neural Network from Scratch I also have written Run Length Encoding from Scratch and you can give it a try if you’d […]

## 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 […]