The Naïve Bayes Classifier uses the probability method as the statistical basis it uses.
For example, we have frame data regarding a text whether it is talking about sports or not.
Then there is one test of the following data: “A very close game” and the question is where the sentence falls into the classification.
So, mathematically we want P (sports | a very close game) which corresponds to the written word as the probability of the sports tag if given the sentence “a very close game”
Naïve Bayes is based on the Bayes Theorem. …
In general, there are two frameworks that are commonly used by data scientists to gather information and create models from raw data. Commonly used methods include the Cross-industry Standard Process for Data Mining (CRISP-DM) and Obtain, Scrub, Explore, Model, and Interpret (OSEMN) Framework. I will explain the use of CRISP-DM and its use directly in the program that has been created.
CRISP-DM was first introduced in 1996 when computer capabilities and tools were still limited. The desire to produce data analysis and a good model then prompted several large companies at that time, SPSS and Tetradata, and their current users…
One way to store data in a non-relational form such as tweets from Twitter is to store it with non-relational databases such as MongoDB or Cassandra. On this occasion, the author will demonstrate how data storage Apache Kafka receives and then saves to MongoDB using the help of the pymongo package.
· Apache Kafka
· Jupyter Notebook
Before you start the integration between Kafka and MongoDB, you are required to install pymongo using the following syntax:
Start by running Apache Kafka installed on your system. …
On this occasion, I will explain the use of Python scripts to produce data for Kafka Producer using a fake pizza-based dataset to then be pushed into the Kafka Topic.
Some of the terms commonly used include the following:
· Apache Kafka: a platform used for data transfer using a publish-subscribe messaging system between processes, applications, and servers.
· Topic: It is a storage medium for received data. Topics are similar to tables in the database concept
· Kafka Producer: an application that publishes data into the Topic
I will use Aiven’s Project with a slight modification to the Jupyter…