MongoDB – Commands to Check the Status of MongoDB Database
This article represents different commands which can be used to check the status of MongoDB database on Linux/Ubuntu. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. MongoDB Status Check Commands The following represents some of the commands that can be used to check the status of MongoDB database. Note that mongod represents the daemon process of MongDB databass and, primarily, used to manage database access. It is recommended to check the log file (/var/log/mongo/mongo.log) to get details. Following are some of the commands which can be used to get the status of Mongodb: service mongod status: Displays the status …
Logit vs Probit Models: Differences, Examples
Logit and Probit models are both types of regression models commonly used in statistical analysis, particularly in the field of binary classification. This means that the outcome of interest can only take on two possible values / classes. In most cases, these models are used to predict whether or not something will happen in form of binary outcome. For example, a bank might want to know if a particular borrower might default on loan or otherwise. In this blog post, we will explain what logit and probit models are, and we will provide examples of how they can be used. As data scientists, it is important to understand the concepts …
Linear Regression Cost Function: Python Example
Linear regression is a foundational algorithm in machine learning and statistics, used for predicting numerical values based on input data. Understanding the cost function in linear regression is crucial for grasping how these models are trained and optimized. In this blog, we will understand different aspects of cost function used in linear regression including how it does help in building a regression model having high performance. What is a Cost Function in Linear Regression? In linear regression, the cost function quantifies the error between predicted values and actual data points. It is a measure of how far off a linear model’s predictions are from the actual values. The most commonly …
KNN vs Logistic Regression: Differences, Examples
In this blog, we will learn about the differences between K-Nearest Neighbors (KNN) and Logistic Regression, two pivotal algorithms in machine learning, with the help of examples. The goal is to understand the intricacies of KNN’s instance-based learning and Logistic Regression‘s probability modeling for binary and multinomial outcomes, offering clarity on their core principles. We will also navigate through the practical applications of K-NN and logistic regression algorithms, showcasing real-world examples in various business domains like healthcare and finance. Accompanying this, we’ll provide concise Python code samples, guiding you through implementing these algorithms with datasets. This dual focus on theory and practicality aims to equip you with both the understanding …
6 Types of Brainstorming Techniques for Ideas Generation
Last updated: 1st Dec, 2023 Generating innovative and creative ideas is a key component of success in many fields, from business and marketing to science, technology, and the arts. However, the process of coming up with new and unique ideas can be challenging, especially when faced with deadlines, limited resources, or creative blocks. This is where brainstorming or mindstorming comes into picture. Fortunately, there are several different types of brainstorming techniques that can help individuals and teams generate great ideas and innovate. While brainstorming is one of the most effective techniques out there, not all brainstorming sessions are created equal. The question that is frequently asked is how to brainstorm for effective …
Python – How to Create Scatter Plot with IRIS Dataset
Last updated: 1st Dec, 2023 In this blog post, we will be learning how to create a Scatter Plot with the IRIS dataset using Python. The IRIS dataset is a collection of data that is used to demonstrate the properties of various statistical models. It contains information about 50 observations on four different variables: Petal Length, Petal Width, Sepal Length, and Sepal Width. As data scientists, it is important for us to be able to visualize the data that we are working with. Scatter plots are a great way to do this because they show the relationship between two variables. In this post, we learn how to plot IRIS dataset …
Chebyshev’s Theorem: Formula & Examples
Chebyshev’s theorem is a fundamental concept in statistics that allows us to determine the probability of data values falling within a certain range defined by mean and standard deviation. This theorem makes it possible to calculate the probability of a given dataset being within K standard deviations away from the mean. It is important for data scientists, statisticians, and analysts to understand this theorem as it can be used to assess the spread of data points around a mean value. What is Chebyshev’s Theorem? Chebyshev’s Theorem, also known as Chebyshev’s Rule, states that in any probability distribution, the proportion of outcomes that lie within k standard deviations from the mean …
AIC in Logistic Regression: Formula, Example
Have you as a data scientist ever been challenged by choosing the best logistic regression model for your data? As we all know, the difference between a good and the best model while training machine learning model can be subtle yet impactful. Whether it’s predicting the likelihood of an event occurring or classifying data into distinct categories, logistic regression provides a robust framework for analysts and researchers. However, the true power of logistic regression is harnessed not just by building models, but also by selecting the right model. This is where the Akaike Information Criterion (AIC) comes into play. In this blog, we’ll delve into different aspects of AIC, decode …
Types of SQL Joins: Differences, SQL Code Examples
Structured Query Language (SQL) is one of the most important and widely used tools for data manipulation. It allows users to interact with databases, query and manipulate data, and create reports. One of SQL’s most important features is its ability to join tables together in order to enrich, compare and analyze related data. These joins are termed as inner join, outer join, left join and right join. In this article, we will discuss the different types of joins available in SQL, their differences and provide examples of how each can be used. What is SQL Join? SQL Joins are a technique used in Structured Query Language (SQL) to combine two …
30+ Logistic Regression Interview Questions & Answers
Last updated: 29th Nov, 2023 This page lists down the practice tests / interview questions and answers for Logistic regression in machine learning. Those wanting to test their machine learning knowledge in relation with logistic regression would find these practice tests very useful. The goal for these practice tests is to help you check your knowledge in logistic regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful. These test primarily focus on …
Standard Deviation vs Standard Error: Formula, Examples
Understanding the differences between standard deviation and standard error is crucial for anyone involved in statistical analysis or research. These concepts, while related, serve different purposes in the realm of statistics. In this blog, we will delve into their differences, applications in research, formulas, and practical examples. Introduction to Standard Deviation & Standard Error At the heart of statistical analysis lies the need to understand and quantify variability. This is where standard deviation and standard error come into play. What’s standard deviation? Standard Deviation is a measure that reflects the amount of variation or dispersion within a dataset. It indicates how much individual data points deviate from the mean (average) …
Coefficient of Variation vs Standard Deviation
Last updated: 28th Nov, 2023 Understanding the difference between coefficient of variation (CV) and standard deviation (SD) is essential for statisticians and data scientists. While both concepts measure variability in a dataset, they are calculated differently and can be used in different scenarios for better understanding. Here, we will explore the coefficient of variation vs standard deviation differences to gain a better understanding of how to use them. Coefficient of Variation vs Standard Deviation Coefficient of Variation (CV) is a measure that is used to compare the amount of variation in a dataset relative to its mean value. It is calculated by taking the standard deviation divided by the mean, then …
Classification Problems in Machine Learning: Examples
In this post, you will learn about some popular and most common real-life examples of machine learning (ML) classification problems. For beginner data scientists, these examples of classification problems will prove to be helpful to gain perspectives on real-world problems which can be solved using classification algorithms in machine learning. This post will be updated from time-to-time to include interesting examples which can be solved by training classification models. Before going ahead and looking into examples, let’s understand a little about what is an ML classification problem. You may as well skip this section if you are familiar with the definition of machine learning classification problems & solutions. You may …
Z-test vs T-test vs Chi-square test: Differences, Examples
In the world of data science, understanding the differences between various statistical tests is crucial for accurate data analysis. Three most popular tests – the Z-test, T-test, and Chi-square test – each serve specific purposes. This blog post will delve into their definitions, types, formulas, appropriate usage scenarios, and the Python/R packages that can be used for their implementation, along with real-world examples. Check out a detailed post on the differences between Z-test vs T-test. Definition: What’s Z-test vs T-test vs Chi-square test? The following represents the definition of each of the tests along with a real-world example: Z-test: The Z-test is a statistical test used to determine if there …
What is Web3.0? Features, Design, Skills, NFTs
Last updated: 27th Nov, 2023 What is Web3.0? Web3.0 is the next phase of the internet, which focuses on decentralization and security. It includes new technologies like blockchain, which is revolutionizing how we interact with the internet. To be successful in this new era of the Web 3.0 internet, you will need to have a variety of different skills. In this blog post, we will discuss what those skills are and how you can acquire them! What is Web 3.0? Web 1.0 was characterized by its static content delivery, offering a largely read-only experience to users. In contrast, Web 2.0 marked a significant shift towards interactivity, user-generated content, and the …
Learning Curves Python Sklearn Example
Last updated: 26th Nov, 2023 In this post, you will learn about how to use learning curves to assess the improvement in learning performance (accuracy, error rate, etc.) of a machine learning model while implementing using Python (Sklearn) packages. Knowing how to use learning curves will help you assess/diagnose whether the model is suffering from high bias (underfitting) or high variance (overfitting) and whether increasing training data samples could help solve the bias or variance problem. You may want to check some of the following posts in order to get a better understanding of bias-variance and underfitting-overfitting. Bias-variance concepts and interview questions Overfitting/Underfitting concepts and interview questions What are learning curves? …
I found it very helpful. However the differences are not too understandable for me