In this article, we will discuss some basic visualization with matplotlib and seaborn library. Both libraries are well known in the data science and analytics community.
Some examples of visualization with matplotlib…
This article will change the new beginners’ thoughts to learn natural language processing (NLP). When I started learning natural language processing first time is always something that how I will use all these concepts.
The prerequisite for this article is the basic knowledge of natural language concepts. You can read the below article to brush up on the concepts.
Reading sentiment text file
importing all the necessary libraries.
import pandas as pd import numpy…
This article will provide the all depth concepts of the list as a part of the data structure. The concepts will go from basic to advance to know the inside-out of the list.
The first question raise in our mind is what is a list?
The following points will make you understand the list as shown below:
In this article, we will discuss time series concepts with machine learning examples that deal with the time component in the data.
Forecasting is so much important in the banking sector, weather, population prediction, and many more that directly deals with real-life problems.
Time series models are based on a function of time. The measurements are in regular intervals of time where time be an independent variable for modeling.
Z = f(t)
Z is the values Z1, Z2……Zn and “t” are the times at T1, T2….Tn intervals.
This article is related to find the prediction that person is diabetic or not based on given data. We will use two machine learning approaches to find the accuracy of prediction.
The data contains 8 independent variables and 1 dependent variable. The inspiration to make the prediction model to ease the working in less time and make a fast prediction for further medication.
The independent variables are: pregnancies, glucose, BMI, insulin, blood pressure, skin thickness, pedigree function, age
The dependent variable: outcome
This article will cover all the concepts related to functions and make you feel comfortable in programming. This topic is very easy to understand and yet difficult because of less practice.
The worth of using function comes to know when you are writing the formula more than one or more times in a program o algorithm and it cost time.
It is important to make a single-function comprise of that formula and use these functions many times.
The benefits of using…
In this article, we will discuss error handling in python with a try, except and finally keywords to handle file and data management.
In general, the errors describe in these three categories as shown below:
Another article in the series of Fully Explained machine learning algorithms i.e. BIRCH clustering in unsupervised learning.
This algorithm is used to perform hierarchical clustering based on trees. These trees are called CFT i.e. Cluster Feature Trees. The full form of BIRCH is Balanced Iterative Reducing Clusters using Hierarchies. The use case of BIRCH clustering is in below scenario:
The metric use in this cluster to measure the distance is Euclidean distance measurement.
There are some points that BIRCH is very useful in clustering algorithms as shown below:
In this article, we will discuss how to create a fake estimator just to compare with the model estimator. We will discuss two types of dummies in supervised learning i.e. regression and classification.
This concept comes in the metrics and scoring part of sklearn.
It is used to make predictions on a simple rule to know the simple baseline for compare regressors but not use in real problems.
Parameters in DummyRegressor
There are main parameters as shown below:
This article will be fun for all readers
Hypotheses testing is an idea to be tested in statistics on observed data points. It is all about guessing the things that can be work or not to make meaningful results.
A good hypothesis contains “if” and “then” words. For example, if the temperature is increased then the solid will melt.
When we always do hypotheses we have to know what is our null hypothesis. For example, if we say the…