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Showing posts from January, 2023

Machine learning interview questions

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1 . What is outliers , How to locate them , what are the  treatment methods  Outliear -  A value that "lies outside " (is much smaller or longer than ) most of the value in set of data  Example -  23, 29, 32, 3, 27, 83, 28                      both 3 and 83 are outlier There are several methods for locating outliers in a dataset including Visualization - ploting the data on a graph and visually inspecting it can often reveal outliers  Z- Scores - A z-score is a measure of how many standard deviation a data point with a z-score greater than or less than -3 are considered outliers  Interquartile Range - The IQR is the difference between the 75th and 25th percentiles of a dataset . Data points that are more than 1.5 times the IQR below the first quartile or above the third quatile are considered outliers  Mahalanobis distance - This methods calculate the distance of each data point from the me...

SQL - Structured Query Language

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SQL stand for stuctured query language  sql is a language designe specifically for communicting with database  this is a strandard language used to preform task such as retieval update insertion and deletion of data from a database  sql is an ANSI (american national standrad institute ) standard Why use sql ? SQL (Structured Query Language) is used to communicate with and manipulate databases. It is used to insert, update, and retrieve data from a database, as well as to create and modify the structure of a database. It is a standard language for interacting with relational databases and is widely used in data analysis and management systems. It is also easy to learn, simple to use and efficient in managing large amounts of data. What we do with sql ? SQL (Structured Query Language) is a programming language used to manage and manipulate data in a relational database management system (RDBMS). Here are a few things you can do with SQL: Create and modify databases: Use SQ...

Python

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What is python? "Python is a popular programming language. It was created by Guido van Rossum, and released in 1991" Python is  a computer programming language often used to build websites and software, automate tasks, and conduct data analysis . Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.                    Do with python  Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick. Python can be treated in a procedural way, an object-oriented way or a functional way. Python use for Ai and ...

About - Data science

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Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data. This analysis helps data scientists to ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results. Data science is important because it combines tools, methods, and technology to generate meaning from data. Modern organizations are inundated with data; there is a proliferation of devices that can automatically collect and store information. Online systems and payment portals capture more data in the fields of e-commerce, medicine, finance, and every other aspect of human life. We have text, audio, video, and image data available in vast quantities.    Data science average salary in diffrent country Data science salaries vary widely depending o...

Data science vs Data analytics

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Difference between Data science and Data analytics Data science is a broad field that encompasses various techniques and tools used to extract insights and knowledge from data. It involves using statistical, machine learning, and programming methods to analyze and interpret large sets of data. Data science also involves the use of visualization and communication techniques to present findings and make data-driven decisions. Data analytics, on the other hand, is a subset of data science that focuses on the analysis and interpretation of data. It involves using tools and techniques to extract insights and knowledge from data, such as statistical analysis, data mining, and visualization. Data analytics is often used in business and industry to make data-driven decisions and improve operations. In summary, data science is a broader field that includes data analytics as well as other techniques, while data analytics is a specific application of data science that focuses on the analysis and ...

Data Analysis

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  What is data analysis? Data analysis is the process of examining, cleaning, transforming, and modeling data to extract useful information, draw conclusions, and support decision-making. It involves using statistical, computational, and visualization techniques to identify patterns, trends, and insights within large sets of data. Data analysis can be applied to various fields, such as business, healthcare, finance, and social sciences, to inform strategic planning, improve operations, and drive innovation. Data analytics Data analytics is the process of analyzing and interpreting large sets of data to uncover patterns, trends, and insights that can inform decision-making and strategy. This process involves collecting, cleaning, and organizing data, as well as using statistical and computational methods to analyze the data and extract meaningful information. Data analytics can be applied in a variety of fields, including business, ...