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 […]

# data analysis

## 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 […]

## Different method of Outliers Detection

Outlier is a data point that is significantly different from the other data points in a sample. Outliers can occur for a variety of reasons, such as errors in measurement or recording, or they can be the result of natural variation in the data. Outliers can have a significant effect on the statistical properties of […]

## 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 […]

## 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 LSTM

LSTMS are a variety of RNNs but lets start with RNNs. RNNs are unable to remember long-term dependencies in time series data because of the vanishing gradient issue. An RNN version called LSTM was created to deal with this problem. Similar to RNN, LSTM features a hidden state that functions as short-term memory. Additionally, it […]

## Apache Superset for COVID Dashboards

Apache Superset is a very useful and easy-to-use visualization and dashboard-making tool that can be an alternative to tools like Tableau and PowerBI. In this blog, we will explore how we can create awesome data dashboards using Apache superset with little to no code at all. But there are a few things one should do […]

## Monte Carlo Simulations in R

Monte Carlo Simulations What is Monte Carlo Simulations? One of the main motivations to switch from spreadsheet-type tools (such as Microsoft Excel) to a program like R is for simulation modeling. R allows us to repeat the same (potentially complex and detailed) calculations with different random values over and over again. Within the same software, […]