1596547680
The Ultimate Guide To SMS: Spam or Ham Detector
TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithms and develop the Python Flask App.
The blog is a series of the blog post, if you haven’t read the theoretical Artificial Intelligence concept of spam or ham classifier, please take a ten-minute read at:
The Ultimate Guide To SMS: Spam or Ham Detector
Detailed Report for Developing Spam or Ham Classifier: Part 1
We have covered in Part 1
- Theoretical AI Concept Regarding Spam or Ham Classifier
- Classification Algorithms
We will cover here in Part 2
- Exploring Data Source
- Data Preparation
- Exploratory Data Analysis
We will cover in next Part 3
- Naïve Bayes Behind Spam or Ham
- Performance Measurement Criterion
- Development of Spam or Ham Detector
Exploring Data Source
The dataset is originally sourced from Tiago A. Almeida (talmeida ufscar.br) Department of Computer Science Federal University of Sao Carlos (UFSCar) Sorocaba, Sao Paulo — Brazil and taken from UCI Machine Learning [15].
The collection is composed by just one text file, where each line has the correct class followed by the raw message.
#data-science #python #artificial-intelligence #sms #spam
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1596718980
The Ultimate Guide To SMS: Spam or Ham Detector
TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithms and develop the Python Flask App.
The blog is a series of the blog post, if you haven’t read the theoretical Artificial Intelligence concept of spam or ham classifier and have not worked with algorithms in jupyter notebook, please explore it at:
The Ultimate Guide To SMS: Spam or Ham Detector
Detailed Report for Developing Spam or Ham Classifier: Part 1
The Ultimate Guide To SMS: Spam or Ham Detector
Detailed Report For Developing Spam or Ham Classifier: Part 2
We have covered in part 1 & 2
- Theoretical AI Concept Regarding Spam or Ham Classifier
- Classification Algorithms
- Exploring Data Source
- Data Preparation
- Exploratory Data Analysis
We will cover here in Part 3
- Naïve Bayes Behind Spam or Ham
- Performance Measurement Criterion
- Development of Spam or Ham Detector
Designed by Author. Illustration from unDraw.
Naïve Bayes Behind Spam or Ham
One of the most useful applications of the Bayes rule is the so-called naive Bayes classifier.
The Naïve Bayes algorithm creates a probabilistic model for classification of SMS messages. Even though all features contribute towards the overall probability of classification, Naïve Bayes algorithm assumes that the features are statistically independent of each other[10]. Although this assumption may not hold true for all cases, Naïve Bayes algorithm has shown promising results in comparison with other well-known classification algorithms. An advantage of Naïve Bayes is that it only requires a small amount of training data to estimate the parameters necessary for classification and as small dataset size Naïve Bayes classifiers can outperform the more powerful alternatives[18]. Because independent variables are assumed, only the variances of the variables for each class need to be determined and not the entire covariance matrix.
#sms #python #spam #data-science #artificial-intelligence
1596544440
The Ultimate Guide To SMS: Spam or Ham Detector
TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithm and develop the Python Flask App for SMS: spam or ham detector.
Short Message Services (SMS) is far more than just a technology for a chat. SMS technology evolved out of the global system for mobile communications standard, an internationally accepted[1]. Spam is the abuse of electronic messaging systems to send unsolicited messages in bulk indiscriminately [2]. While the most widely recognized form of spam is email spam, the term is applied to similar abuses in other media and mediums. SMS Spam in the context is very similar to email spams, typically, unsolicited bulk messaging with some business interest. SMS spam is used for commercial advertising and spreading phishing links. Commercial spammers use malware to send SMS spam because sending SMS spam is illegal in most countries. Sending spam from a compromised machine reduces the risk to the spammer because it obscures the provenance of the spam. SMS can have a limited number of characters, which includes alphabets, numbers, and a few symbols. A look through the messages shows a clear pattern. Almost all of the spam messages ask the users to call a number, reply by SMS, or visit some URL. This pattern is observable by the results obtained by a simple SQL query on the spam corpus[3]. The low price and the high bandwidth of the SMS network have attracted a large amount of SMS spam [4].
People classify SMS Spam as annoying (32.3%), wasting time(24.8%), and violating personal privacy (21.3%)[5].
Every time SMS spam arrives at a user’s inbox, and the mobile phone alerts the user to the incoming message. When the user realizes that the message is unwanted, he or she will be disappointed, and also SMS spam takes up some of the mobile phone’s storage.
SMS spam detection is an important task where spam SMS messages are identified and filtered. As more significant numbers of SMS messages are communicated every day, it is challenging for a user to remember and correlate the newer SMS messages received in context to previously received SMS. Thus, using the knowledge of artificial intelligence with the amalgamation of machine learning, and data mining we will try to develop web-based SMS text spam or ham detector.
This is three parts of blog series, where we will understand the in and out of spam or ham classifier from the aspect of Artificial Intelligence concepts, and work with various classification algorithms in jupyter notebook and select the one algorithm based on performance criteria. Then, we will develop the Python web-based SMS text spam or ham detector.
What will we cover here
- Theoretical AI Concept Regarding Spam or Ham Classifier
- Classification Algorithms
- Exploring Data Source
- Data Preparation
- Exploratory Data Analysis
- Naïve Bayes Behind Spam or Ham
- Performance Measurement Criterion
- Development of Spam or Ham Detector
#spam #sms #data-science #python #artificial-intelligence
1596547680
The Ultimate Guide To SMS: Spam or Ham Detector
TL;DR Understanding spam or ham classifier from the aspect of Artificial Intelligence concepts, work with various classification algorithms, and select high accuracy producing algorithms and develop the Python Flask App.
The blog is a series of the blog post, if you haven’t read the theoretical Artificial Intelligence concept of spam or ham classifier, please take a ten-minute read at:
The Ultimate Guide To SMS: Spam or Ham Detector
Detailed Report for Developing Spam or Ham Classifier: Part 1
We have covered in Part 1
- Theoretical AI Concept Regarding Spam or Ham Classifier
- Classification Algorithms
We will cover here in Part 2
- Exploring Data Source
- Data Preparation
- Exploratory Data Analysis
We will cover in next Part 3
- Naïve Bayes Behind Spam or Ham
- Performance Measurement Criterion
- Development of Spam or Ham Detector
Exploring Data Source
The dataset is originally sourced from Tiago A. Almeida (talmeida ufscar.br) Department of Computer Science Federal University of Sao Carlos (UFSCar) Sorocaba, Sao Paulo — Brazil and taken from UCI Machine Learning [15].
The collection is composed by just one text file, where each line has the correct class followed by the raw message.
#data-science #python #artificial-intelligence #sms #spam
1613800156
Laravel 8 Send SMS to Mobile with Nexmo Tutorial
Laravel 8 send sms using nexmo example. In this tutorial, you will learn how to integrate sms gateway and send sms notification to mobile using nexmo in laravel 8 app.
This tutorial will guide you step by step on how to send send sms to mobile with nexmo in laravel 8 app. Now, You need to follow the some step to done laravel nexmo message.
First of all, visit the following link https://dashboard.nexmo.com/sign-in and create nexmo account. Get client id and secret from nexom account.
https://www.tutsmake.com/laravel-8-send-sms-to-mobile-with-nexmo-example/
#send sms with nexmo on laravel #nexmo message send sms #laravel send sms notification #nexmo sms installation laravel #how to integrate sms gateway in laravel
1593601800
Repository Pattern in ASP.NET Core - Ultimate Guide
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#asp.net core #repository #pattern #ultimate #guide #.net