The cd command is one of most fundamental commands in Bash shell. It is used to change current working directory to a specified location. This command is particularly useful when navigating through file system, especially in situations where you need to access files or directories in a different location. In this article, we will explore how to use cd command in Bash scripts. What is cd Command? Before diving into usage of cd command, it is important to understand what it does. cd command is a built-in command in Bash that is used to change current working directory. When you ... Read More

Introduction Machine Learning and Deep Learning are emerging technologies in the current industry scenario. There is a lot of work related to the industry and significantly impacting the present world business scenario. There are lots of people who are trying to enter this field and want to get benefited. To master one field, it is necessary to get updated on the latest research works and the things happening in the latest days. There is a lot of content available on the internet that can b useful for the same. Still, the approach to reading these machine learning papers should be ... Read More

Overview Python is a high-level language used for many purposes such as developing websites and software, data visualization, data analysis, and task automation. Additionally, it provides top skills for using scientific, statistical, and mathematical functions. And also It offers superb libraries for working with data science applications. In terms of application areas, ML scientists also favour Python. There are numerous data types in Python. The most popular ones are list, dict (dictionary), int (integer), str (string), bool (boolean), and float (floating point). And also there are many libraries that are used in data science NumPy, pandas, Matplotlib, scipy, etc. Python ... Read More

As the world entered the era of big data in recent decades, the demand for more effective and efficient data storage greatly expanded. Businesses that use big data invest a lot of time and energy in creating frameworks that can hold a lot of information. The storage of vast amounts of data was then made possible by the creation of frameworks like Hadoop. As the storage issue can be resolved by using the frameworks the next issue that comes is to process the data that had already been stored. The solution to processing the data and getting the useful information ... Read More

The data science and engineering fields are interacting more and more because data scientists are working on production systems and joining R&D teams. We want to make it simpler for data scientists without prior engineering experience to understand the core engineering best practices. We are building a manual on engineering subjects like Git, Docker, cloud infrastructure, and model serving that we hear data science practitioners think about. Introduction to Git A version control system called Git is made to keep track of changes made to a source code over time. Without a version control system, a collaboration between multiple people ... Read More

Data science is the process of organizing, processing, and analyzing vast amounts of data in order to extract knowledge and insights from them. It involves a number of different fields, including statistical and mathematical modelling, data extraction from its source, and methods for data visualization. Working with big data technology to gather both structured and unstructured data is commonly required. In the parts that follow, we'll examine several applications of data science and how python might be useful there. Python is a widely used high-level, general-purpose, object-oriented, and interpreted language. To utilize Python for a task, one only needs to ... Read More

Python is a general-purpose, object-oriented, interpreted, high-level language and is very popular in the market. Python has a very rich library that contains pre-defined code for almost every purpose and to use python for a task using only needs the logic, as most of the coding part is handled by python itself. Python has a large community of developers which provides an extra benefit to newcomers and the experienced python user that there is no issue with any bugs. Before moving to the introduction of python for data science let’s see some basics of data science. What is Data Science? ... Read More

In natural language processing, the interlingua and transfer techniques are employed to facilitate language translation and other language-related activities. These techniques are valuable because they enable automatic text translation from one language to another, which may be beneficial in a number of scenarios such as international communication or the processing of vast volumes of multilingual text data. In this post, we will examine and contrast the Interlingua Approach with the Transfer Approach. What is the Interlingua Approach? The interlingua approach is a method for translating text from one language to another in natural language processing. Its foundation is the idea ... Read More

Welch's ANOVA, is an expansion of the standard ANOVA test that allows for different sample sizes and variances. Frequently, the samples that are being compared in an ANOVA test may not have comparable variances or sample sizes. In certain situations, Welch's ANOVA should be performed rather than the standard ANOVA test since it can not be acceptable. In this post, we'll take a detailed look at Welch's ANOVA What is Welch’s ANOVA? Welch's ANOVA is a variant of the ANOVA test, which is used to compare the means of two or more samples. ANOVA determines if the means of two ... Read More

ANCOVA (analysis of covariance) is a useful statistical method because it enables the inclusion of covariates in the analysis, which may assist adjust for auxiliary variables and increase the precision of group comparisons. These additional factors, or covariates, may be incorporated into the study using ANCOVA. In order to be sure that any observed differences between the groups are caused by the therapy or intervention under study and not by unrelated factors, ANCOVA can be used to adjust for the impact of the covariates on the group means. This can make the comparisons between the groups more accurate and give ... Read More