Correlation Coefficient is a statistical measure used to measure strength and direction of two or more continuous variables. Correlation Coefficient Correlation Coefficient is used for finding out relationship between two or more variables. Its value ranges between -1 to +1. Negative value would correspond negative correlation, positive value would correspond positive correlation and if value is close to zero then it means there is no correlation between the two continuous variables. Also read : How to detect outliers in python? In this post you will discover seven different correlation coeffi ..read more

Random Number generator in python play an important part of machine learning as they are used for hyperparameter optimization, adjusting weights in deep learning amongst other necessary processes. In this tutorial, you will learn how to work with random number generator in python. After completing tutorial, you will understand: Random Numbers can be generated via pseudorandom number generators. How to use random number generator in Python by using Random Library How to generate random numbers, arrays using Numpy Library in Python Random Number Post Overview This post is divided into three pa ..read more

Numpy exercises give you a good exposure on learning the numpy as it is a base for most of linear algebra calculations in python. There is no particular order in these numpy exercises, it is mostly based what a normal data scientist uses in day to day functioning. Numpy exercises 1) How to import numpy in jupyter notebook? import numpy as np # You can use any defined variable instead of np. 2) How to print numpy version? np.__version__ 3) How to print numpy configuration? np.__config__ 4) How to create a null vector of size 15? np.zeros(15) #Output array([0., 0., 0., 0., 0., 0., 0., 0 ..read more

Speech recognition is interdisciplinary sub-field in natural language processing. It uses sub-field of computer science and computational linguistics. We also know speech recognition’s with various names like speech to text, computer speech recognition and automatic speech recognition. What are different Models, methods, and algorithms used in Speech Recognition? There are various modelling techniques used in speech recognition like acoustic modelling, document classification, statistical machine translation and language modelling. Most of modern general purpose speech recognition’s system ar ..read more

Optical Character recognition is a subset of natural language processing which has available with us for decades. However, over period of time it has evolved into a major tool for reading documents and large scale automation. What is optical character recognition(OCR)? OCR is a process by which we convert typed, printed or hand written text into machine – encoded text. This can be scanned document, images, or any text which is superimposed in a picture. Main idea behind reading data in OCR is that it should be a text within a image. What are different types of CR techniques? Optical Character ..read more

Natural language processing (NLP) is a branch of artificial intelligence which lets computers interpret and understand human language. Natural Language Processing What makes NLP so difficult? In human language, there are written rules which are difficult for a computer to comprehend. The goal is to make sense from written or spoken human interaction and respond or act as a person would act. In current scenarios, chat bots or voice to text application like Siri, Alexa, Cortana are good example. Why is Natural Language Processing Important? In today’s world, 90 percent of data is stored in forms ..read more

Pandas exercise are a really important for analytics professional. Most of the exercises which I have come across on the internet are based on dummy data. In this post, we will use case studies which resembles real world problems. Thereby giving you a practical experience on solving problems at your work, school or wherever you need to use Pandas. So let us get started with Pandas exercise. Pandas Exercise One – UCI Bank Marketing dataset This dataset is related to Portuguese bank and is used from phone calls made through marketing team. We will start from beginning which will cover aspects o ..read more

Pandas exercise are a really important for analytics professional. Most of the exercises which I have come across on the internet are based on dummy data. In this post, we will use case studies which resembles real world problems. Thereby giving you a practical experience on solving problems at your work, school or wherever you need to use Pandas. So let us get started with Pandas exercise. Pandas Exercise One – UCI Bank Marketing dataset This dataset is related to Portuguese bank and is used from phone calls made through marketing team. We will start from beginning which will cover aspects o ..read more

Read_csv in pandas is a function which provides us with ability read, manipulate and write data to and from CSV( comma separated value) files into jupyter notebook, Ipython notebook or python language in general. It is pretty intuitive to use when it works and when it fails, it can pretty problematic. In this post, you will learn following : Importing CSV files with the help of read_csv function in pandas What is a CSV file? Difference between CSV and Text file Difference between CSV and XLS Pros and Cons of CSV Files Common errors while importing CSV file through pandas Photo by Mika Baumei ..read more

Seaborn plot play an important role in machine learning, as by using them we can gain a lot of insights and valuable information regarding your data set. Seaborn Plot End to End Guide In this post, you will learn all the charts in seaborn namely, they are broadly divided into four categories: Relational plot also known as relplot scatterplot Lineplot distributions plot also known as displot histplot kdeplot ecdfplot rugplot categorical plot also known as catplot stripplot swarmplot boxplot violinplot pointplot barplot boxenplot other plots lmplot jointplot pairplot heatmap joint ..read more