A study of regression problem using Decision tree
Decision trees are one of the most commonly used technique among all business analysts. It helps us with the prediction and...
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Classification Problems using Logistic Regression
The classification problem is a type of supervised problem in which the target variable is categorical in nature. In this article, we...
Clustering- Machine learning
In unsupervised learning where we don't have a target variable, we try to find patterns based on their observation, features. Based on...
Selecting the right model- Machine learning
The main aim of any machine learning model is to perform well on unseen data. It is important that the model performs well on training as...
Evaluation metrics- Machine learning
After model building using a different algorithm, we can evaluate the performance of the model using different evaluation metrics....
Train and test a model- Machine learning
Dividing data set into train and test is one method to quickly evaluate the performance of the algorithm on the problem. The training...
Build first predictive model- Machine learning
After completing previous stages of predictive modeling, problem definition, hypothesis generation, data extraction, data exploration, we...
Variable transformation - Data Exploration
What is variable transformation? Variable transformation is a process by which we replace a variable with some function of that variable....
Outlier treatment - Data Exploration
Reason for outliers An outlier is a data point that differs significantly from other observations. The outlier present in the data set...
Techniques of Missing value treatment - Data Exploration
Reasons for missing values in data. Missing values in data are due to many reasons. one of these is non-response, like when you collect...
Univariate and Bivariate Analysis
Univariate Analysis What is a univariate analysis? What is the use of univariate analysis? univariate analysis is when we focus on a...
Data Exploration
What is a data exploration Data exploration is the fourth stage of predictive modeling. This process helps to gain insights from data. A...
Understanding Hypothesis generation and Data Extraction.
After problem definition, the next stage of predictive modeling is hypothesis generation. A hypothesis is an opinion or view of a problem...
STAGES OF PREDICTIVE MODELING
Most of the organizations are heavily investing in advanced analytics and predictive modeling. This can be the motivation for why we have...
INTRODUCTION TO PREDICTIVE MODELING
Predictive modeling is a process that uses past data and other attributes to predict outcomes with the data model. Now with this...
MACHINE LEARNING LIFE CYCLE IN 15 DAYS.
Welcome to this journey of machine learning life cycle in 15 days. Before starting this one should have a bit of programming experience...
Reading Spatialdata using geopandas
Spatial data is the data that identifies the geographic location of features and boundaries on Earth, such as lake, stream, oceans,...
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