Identify the type of star using its characteristics and neural networks.

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Photo by Alex Kunchevsky for OUTLΛNE on Dribbble

Classification of stars based on their characteristics is called stellar classification.

Here we classify them into 6 classes — Brown Dwarf, Red Dwarf, White Dwarf, Main Sequence, Supergiant, Hypergiant.

Implementation of the idea on cAInvas — here!

Dataset

On Kaggle by Deepraj Baidya | Github

The dataset took 3 weeks to collect for 240 stars which are mostly collected from the web. The missing data were manually calculated using equations of astrophysics.

The dataset is a CSV file with characteristics of a star like luminosity, temperature, colour, radius, etc that help classify them into one of the 6 classes — Brown…


Are they being sarcastic?

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Photo by Su for RaDesign on Dribbble

Sarcasm is the use of words that convey a meaning opposite to the one you actually intend to pass on. It has the ability to flip the sentiment of the sentence. This makes sarcasm detection an important part of sentiment analysis.

Most of the datasets available for this purpose rely on tweets written by the public. This can result in noisy data with improper labeling. The context of tweets is dependent on the thread (in case of replies) and thus, understanding the context of the conversation becomes crucial to labeling the text.

To overcome this, here we use a dataset…


Are they being sarcastic?

Image for post
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Photo by Su for RaDesign on Dribbble

Sarcasm is the use of words that convey a meaning opposite to the one you actually intend to pass on. It has the ability to flip the sentiment of the sentence. This makes sarcasm detection an important part of sentiment analysis.

Most of the datasets available for this purpose rely on tweets written by the public. This can result in noisy data with improper labeling. The context of tweets is dependent on the thread (in case of replies) and thus, understanding the context of the conversation becomes crucial to labeling the text.

To overcome this, here we use a dataset…


Predict a customer’s behaviour in online shopping websites for KPI and marketing analysis.

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Photo by Karol Cichoń on Dribbble

How do we know if a customer is going to shop or walk away? Understanding the customers is crucial to any seller/store/online platform. This understanding can be important in convincing a customer who is just browsing to buy a product.

In offline stores, the inferences derived influence the placement of objects in the store. When the same experience is translated to an online store, the sequence of web pages browsed to reach a product becomes important.

Here, we analyze the behaviour of customers as they browse through the pages to predict if they will make a purchase or not.

Implementation…


Predicting the age of abalone (sea snails) from their physical measurements.

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Photo by Nico Medina on Dribbble

Abalone is a common name for sea snails. Determining their age is a detailed process. Their shell is cut through the cone, stained and the rings are counted using a microscope.

This is a time-consuming process that can be simplified by using neural networks to predict their age using the physical measurement of the abalone

Here, we use measurements such as length, height, weight, and other features to predict their age.

Implementation of the idea on cAInvas — here!

The dataset

Data comes from an original (non-machine-learning) study: Warwick J Nash, Tracy L Sellers, Simon R Talbot, Andrew J Cawthorn and Wes…


Predict next day rain in Australia using weather data.

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Photo by GRAMM on Dribbble

A weather forecast is a prediction of how the weather will be in the coming days. Air pressure, temperature, humidity, wind, and other measurements are used by meteorologists along with other methods to predict the weather.

Predicting weather requires keen observation skills and knowledge of weather patterns. With trained deep learning models, we can identify the patterns in data to make predictions for the coming days.

Here, we use present-day weather conditions in different cities of Australia to predict rain the next day.

Implementation of the idea on cAInvas — here!

The dataset

On Kaggle by Joe Young and Adam Young

Observations…


Detecting whether a person is confused or not based on the EEG recordings.

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Photo by George Vald on Dribbble

Do students always ask doubts when they are confused? How do you know if someone is confused? Facial expressions, maybe. Confusions happen when we are not able to comprehend what we see/hear.

EEG, which stands for electroencephalography, is a method to record the electrical activity of the brain using electrophysiological monitoring.

This is done through non-invasive (in most cases) electrodes placed along the scalp that records the brain’s spontaneous electrical activity over a period of time.

Here, we track these EEG signals to detect whether a person is confused or not.

Implementation of the idea on cAInvas — here!

The dataset

On…


Finding the category of the question asked, i.e., the type of answer to be given.

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Photo by Mike Mirandi on Dribbble

To answer a question, we need to understand the question and also the type of answer required. Different questions require different formats of answers. Categorizing questions based on answer formats help in addressing the questions better.

For example, a question that starts with ‘how’ requires an answer that describes an event, a process, or procedure. This is called a descriptive answer. Questions with ‘what’ requires an answer that contains entities that fit the characteristics/definition given in the question.

For a conversational AI model, identifying the answer type is as important to answering the question as is understanding the context of…


Identify the breed of the sheep in the image using neural networks.

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Photo by Petter Pentilä on Dribbble

Do you know how many breeds of sheep are out there? Many of us do not know their names, let alone recognizing them. This task requires expertise and becomes easier with experience.

For curious minds, a model that helps recognize the breed of sheep is helpful. As for the expert minds, this is a companion. From keeping count to monitoring their movement, this helps in reducing the time and effort required for the task.

Here, we attempt to classify face-focussed images of sheep into 4 breeds — Marino…


Identifying whether the given text is spam or not (ham).

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Photo by Emanuele Colombo on Dribbble

Spam texts are unsolicited messages usually sent for the purpose of advertising. While this helps a product reach consumers, it can be a source of unwanted input/communication to the consumer.

While reaching out to consumers in mass in order to increase the public presence of their product may seem harmless it is important to remember that spam messages, in many cases, include phishing attempts, non-commercial agenda propagation, or any other prohibited content/intent. These can put the consumer at the receiving end at risk.

There are many ways a spammer can reach you — SMS, calls, e-mails, web search results, etc.

AI Technology & Systems

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