Anar AbiyevinAnalytics Vidhya·Sep 5, 2020Member-onlyMachine Learning — Univariate Linear RegressionLinear Regression (LR) is one of the main algorithms in Supervised Machine Learning. It solves many regression problems and it is easy to implement. This paper is about Univariate Linear Regression(ULR) which is the simplest version of LR. The paper contains following topics: The basics of datasets in Machine Learning; …Machine Learning7 min readMachine Learning7 min read
Anar AbiyevinAnalytics Vidhya·Oct 24, 2020Member-onlyMachine Learning — Multivariate Linear RegressionLinear Regression is among mostly used Machine Learning algorithms. Univariate Linear Regression is the simpler form, while Multivariate Linear Regression is for more complicated problems. This is my second paper about Linear Regression, first one is on Univariate Linear Regression. You can look through it for getting background knowledge on…Machine Learning5 min readMachine Learning5 min read
Anar AbiyevinAnalytics Vidhya·Mar 12, 2021Member-onlyMachine Learning Linear Regression project from scratch (without library)Linear Regression is a Supervised Machine Learning which is used to predict values within a certain range, rather than classifying them into categories. In this article you can find the implementation of Univariate Linear Regression in Python without using any machine learning library. …Machine Learning7 min readMachine Learning7 min read
Anar AbiyevinAnalytics Vidhya·Mar 12, 2021Member-onlyHow to implement Linear Regression using sklearn libraryPython is considered the best programming language for Machine Learning and AI based projects because of its great variety of libraries and frameworks. Scikit-learn is likely the most useful library for Machine Learning in Python. …Machine Learning3 min readMachine Learning3 min read
Anar Abiyev·May 7, 2021Member-onlyMachine Learning Logistic Regression in Python From ScratchClassification is one of the two branches of Supervised Learning. As the name suggests it divides objects into groups or classes based on their features. Logistic Regression is among the most used Classification algorithms. In this paper, I will show the Python implementation of the algorithm. …Machine Learning8 min readMachine Learning8 min read
Anar AbiyevinAnalytics Vidhya·Mar 3, 2022Member-onlyData Science Regression Project ExampleThis is Data Science Regression case study and aims to show how to apply data science tools on real project in Python. For better understanding and clarification the blog has been organized as separate parts (like data understanding, EDA, modelling, etc.). Both code and explanation have been provided. Hope this…Data Science9 min readData Science9 min read
Anar Abiyev·Mar 11, 2022Member-onlyData Science Movie Recommendation System — Theory and Simple Python ImplementationEven if being aware of or not, we come across recommendation systems everyday while using social media. The most famous companies using such systems are Amazon, Netflix, YouTube and etc. Recommendation systems play important role in the business of these corporations. …Data Science4 min readData Science4 min read
Anar AbiyevinAnalytics Vidhya·Mar 13, 2022Member-onlyComplete Guide to Exploratory Data Analysis with Python PlotlyIntroduction Exploratory data analysis is the key method to extract useful insights from data which play important role in the selection of model, data preprocessing steps, interpretation of results and etc. In this blog, I will dive into details of EDA with the example of car prediction dataset. You can also…Python4 min readPython4 min read
Anar AbiyevinAnalytics Vidhya·Mar 19, 2022Member-onlyStreamlit App for Exploratory Data AnalysisAutomate EDA in Data Science Projects — In every data science problem or project, exploratory data analysis is an irreplaceable part of the workflow. EDA is the step in which you get insights about the dataset. Hence without enough information of dataset, the right choice of model cannot be made. After working with sufficient number of datasets…Data Science4 min readData Science4 min read
Anar AbiyevinAnalytics Vidhya·Mar 25, 2022Member-onlyComplete Guide to Data Cleaning with PythonLearn how to do Data Cleaning step-by-step — I am pretty sure you have heard this famous data science quote: Data Cleaning takes 90% of time in Data Science Projects. If you haven’t, then keep in mind that data cleaning is bread and butter of data science workflow. As people are what they eat (another famous quote), machine…Data Science6 min readData Science6 min read
Anar Abiyev·Sep 22Member-onlyLearn about Data Types in Data Science for beginnersIf you have newly started your data science and/or machine learning journey, you have probably come out to the word “data type”. If you had expressions like the below picture, then you have come to the right place to clear all your confusion! If you enjoy the article, do not forget to clap and follow for more content about deep learning and data science. Let’s go! The graphic below highlights the main classification of data types in data science.Data Science3 min readData Science3 min read
Anar AbiyevinDataDrivenInvestor·Sep 22Member-onlyComplete Guide to Classification Metrices in Data ScienceIf you feel confused about recall, precision, accuracy and other classification metrics, this paper will guide you with high quality examples for better understanding! In this tutorial you will learn what is accuracy. precision. recall. f1 score. You can also check “Overall” at the end of the paper for quick…Data Science4 min readData Science4 min read
Anar AbiyevinPython in Plain English·Sep 22Member-onlyThree Methods to Find Outliers of Data in PythonIn this tutorial, you will learn theoretical and practical knowledge behind the three methods to find outliers in the dataset. — Interquartile range method. Standard deviation method. Z score method. You can find the link to the notebook of the codes of the tutorial at the end of the paper! If you enjoy the article, do not forget to clap and follow for more content about deep learning and data science.Data Scien3 min readData Scien3 min read
