Bokeh is a powerful data visualization library in Python that helps to create interactive and unique visualizations for the web. Bokeh supports various rendering techniques and provides a wide range of built-in tools for creating complex visualizations with multiple glyphs. This document will guide you through the process of creating a plot with multiple glyphs using Bokeh. This plot combines different glyphs to display multiple data series in a single plot that provides a more efficient way to understand the relationship between different variables. What are Glyphs and what are the key advantages of these? Glyphs are graphical representations ... Read More

In big data analysis, PySpark is a stack that combines the popular programming language Python with the open-source big data framework Apache Spark. PySpark provides an excellent interface for big data analysis, and one important component of this stack is Spark's DataFrame API. Here, we'll provide a technical guide for those who want to create PySpark DataFrames, including helpful tips and real-world examples. What are the key advantages of pyspark and which industries mostly use it? Pyspark is a Python API for Apache Spark, which is a distributed computing framework that provides fast, scalable, and fault-tolerant data processing. Some ... Read More

Bokeh is a powerful data visualization library in Python that helps to create interactive and unique visualizations for the web. Bokeh supports various rendering techniques and provides a wide range of built-in tools for creating complex visualizations with multiple glyphs. This document will guide you through the process of creating a plot with multiple glyphs using Bokeh. This plot combines different glyphs to display multiple data series in a single plot that provides a more efficient way to understand the relationship between different variables. What are the key benefits of range slider? Interactive − RangeSlider provides an interactive way ... Read More

A Pandas DataFrame is a two-dimensional table with rows and columns that are immutable, meaning they cannot be changed once they are created. Creating a DataFrame from scratch with lists is a common task in data science and information technology. A list is an ordered collection of elements, and it is one of the most commonly used data structures in Python. A list can store any type of values such as numbers, strings and boolean values. In this document, I will provide a detailed explanation of how to create Pandas DataFrame from lists with real-world examples using step-by-step instructions, code ... Read More

In today's data-driven world, having efficient ways to handle data is essential, and SQLite is one of the best solutions for small-scale database systems. SQLite is a popular relational database system, that is easy to use, lightweight, and scalable. One way to store data in SQLite, is to store it in CSV format. This allows us to store structured data in flat files, which can be easily parsed with the help of Python. In this tutorial, we will learn how to create a SQLite database from CSV files, using Python. What is a SQLite Database? SQLite is a software library ... Read More

A Vehicle Identification Number (VIN) is a unique 17-digit code assigned to every vehicle manufactured after 1981. It contains information about the vehicle’s make, model, year of manufacture, country of origin, and other relevant details. In this instruction manual, we will learn how to create a Graphical User Interface (GUI) using Python programming language to extract vehicle information from a VIN number. Prerequisites Before we dive into the details of creating a GUI, you should have a basic understanding of Python programming, object-oriented programming (OOP) concepts, and how to work with the Tkinter module. List of recommended settings pip ... Read More

Shattering is a key notion in machine learning that refers to a classifier's capacity to accurately distinguish any arbitrary labeling of a group of points. Strictly speaking, a classifier breaks a collection of points if it can divide them into all viable binary categories. The greatest number of points that a classifier is capable of shattering is specified by the VC dimension, which measures a classifier's ability to classify data. For practitioners of machine learning, it is essential to comprehend the idea of shattering and the VC dimension. In this post, we will closely look at shattering a set points ... Read More

The Bayes Theorem, a cornerstone of probability theory, enables the computation of conditional probabilities. The idea behind the theorem is that opinions or previous knowledge change when new information comes to light. The Bayes Theorem has grown in significance in the area of machine learning because it enables the inclusion of previous information into statistical models, producing predictions that are more precise. Application areas for the Bayes Theorem in machine learning include spam detection, medical diagnosis, picture recognition, and natural language processing. Bayes Theorem has developed into a crucial tool for creating precise and effective machine learning models by offering ... Read More

In the field of machine learning, the train-test split is a straightforward yet effective method. In essence, it entails separating your dataset into two separate sets, one for training your model and the other for evaluating its correctness. The efficiency of your model's predictions in light of fresh data may be assessed using this method. You can evaluate how effectively a model generalizes and, consequently, how well it will perform in the real world by giving it a brand-new dataset that it has not been trained on. The train-test split essentially acts as a "reality check" for the capabilities of ... Read More

Data analysis and understanding depend heavily on data visualization. There are several libraries available for the popular programming language Python that might aid with data visualization. Data scientists regularly use meshgrid() and contourf() to produce 2D and 3D graphs because they are excellent tools for facilitating the display of complicated data sets. For building point grids for various visualizations, like heat maps and contour plots, Meshgrid() is a very useful method. We will talk about two crucial methods in this blog post: meshgrid() and contourf (). These methods are essential for two-dimensional visualization of three-dimensional data. What is Meshgrid()? Meshgrid() ... Read More