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The Simplest Regression Learning Algorithm

Linear Regression is a popular regression algorithm that learns a model which is a linear combination of features in the input example.

In this article, we will understand what is regression, how is a Linear Regression Algorithm formed, variations of Linear Regression, and implement it using a tryout python code.

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DEEP LEARNING, NEURAL NETWORKS

The most common types of Neural Networks and their applications

Neural networks are robust deep learning models capable of synthesizing large amounts of data in seconds. There are many different types of neural networks, and they help us in a variety of everyday tasks from recommending movies or music to helping us buy groceries online.

Similar to the way airplanes…

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HANDS-ON TUTORIALS, MACHINE LEARNING PROJECT

Applying natural language processing for sentiment analysis

In the field of social media data analytics, one popular area of research is the sentiment analysis of Twitter data. Twitter is one of the most popular social media platforms in the world, with 330 million monthly active users and 500 million tweets sent each day. By carefully analyzing the…

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Hands-on Tutorials, Deep Learning

Creative application of Machine Learning

Deep Learning has improved many aspects of our lives, in ways both obvious and subtle. Deep learning plays a key role in processes such as movie recommendation systems, spam detection, and computer vision. Though there is ongoing discussion around deep learning as a black box and the difficulty of training…

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Hands-on Tutorials, MACHINE LEARNING

Step by step guide to building a simple recommendation system

Have you ever wondered how YouTube recommends content, or how Facebook recommends you, new friends? Perhaps you’ve noticed similar recommendations with LinkedIn connections, or how Amazon will recommend similar products while you’re browsing. All of these recommendations are made possible by the implementation of recommender systems.

Recommender systems encompass a…

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MACHINE LEARNING

Seven key factors to consider when implementing an algorithm

For any given machine learning problem, numerous algorithms can be applied and multiple models can be generated. A spam detection classification problem, for example, can be resolved using a variety of models, including naive bayes, logistic regression, and deep learning techniques like BiLSTMs.

Having a wealth of options is good…

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Hands-on Tutorials, DEEP LEARNING PROJECT

Applying NLP and Deep Learning for Spam Detection

Have you ever wondered how a machine translates language? Or how voice assistants respond to questions? Or how mail gets automatically classified into spam or not spam?

All these tasks are done through Natural Language Processing (NLP), which processes text into useful insights that can be applied to future data…

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The most important & fundamental concepts in statistics

Beginners usually ignore most foundational statistical knowledge. To understand different models, and various techniques better, these concepts are essential. These work as baseline knowledge for various concepts involved in data science, machine learning, and artificial intelligence.

Here is the list of concepts covered in this article.

  1. Measures of central tendency

Ramya Vidiyala

Interested in computers and machine learning. Likes to write about it | https://www.linkedin.com/in/ramya-vidiyala/

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