Automate 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…

Introduction 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…

Even 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. If you suggest the right product to the customer…

This 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…

Classification 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. It will continue step-by-step…

Yəqin ki, hamımız dedektiv janrda yazılmış əsərlərlə tanışıq. Dedektiv problem ilə tanış olur, daha sonra sorğu-sual edərək məlumatlar toplayır və sonda həmin məlumatlar arasında məntiqi uyğunluq quraraq qatilin kim olduğunu tapır. Bəzən bizə lazım olan bütün informasiyanı bilsək də, problemi həll etmək üçün bu kifayət etmir. Həmin məlumatları sistemləşdirməli, hansının…

Python 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. The sklearn library has a lot of efficient tools for machine learning and statistical modeling…

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. The code will be explained step-by-step with…

Linear 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…