Use Cases

Here you’ll find everything about AI use cases, including Python tutorials on implementing specific use cases.

A machine learning use case is a specific application or instance of using algorithms and techniques to solve a problem or accomplish a task. It typically involves a combination of data preparation, model selection, training, and deployment. AI and machine learning are closely related. In fact, machine learning is a subset of AI, which refers to the use of algorithms and statistical models to enable a system to improve and learn from data over time. In other words, machine learning algorithms allow AI systems to automatically learn and improve from experience, without being explicitly programmed. AI can be applied in a wide range of industries and applications. Some common examples of AI in action include virtual assistants like Siri and Alexa, which use natural language processing to understand and respond to user requests. Another example is self-driving cars. They use a combination of computer vision and machine learning algorithms to navigate roads and traffic. Additionally, AI is often used in healthcare, finance, and other industries. In all these industries, AI improves decision-making, automate processes, and enhance the customer experience. 

Mastering Multivariate Stock Market Prediction with Python: A Guide to Effective Feature Engineering Techniques

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Are you interested in learning how multivariate forecasting models can enhance the accuracy of stock market predictions? Look no further! While traditional time series data provides valuable insights into historical trends, multivariate forecasting models utilize additional features to identify patterns and predict future price movements. This process, known as “feature engineering,” is a crucial step … Read more

Training a Sentiment Classifier with Naive Bayes and Logistic Regression in Python

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Are you ready to learn about the exciting world of social media sentiment analysis using Python? In this article, we’ll dive into how companies are leveraging machine learning to extract insights from Twitter comments, and how you can do the same. By comparing two popular classification models – Naive Bayes and Logistic Regression – we’ll … Read more

Stock Market Prediction using Multivariate Time Series and Recurrent Neural Networks in Python

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Regression models based on recurrent neural networks (RNN) can recognize patterns in time series data, making them an exciting technology for stock market forecasting. What distinguishes these RNNs from traditional neural networks is their architecture. It consists of multiple layers of long-term, short-term memory (LSTM). These LSTM layers allow the model to learn patterns in … Read more

Classifying Purchase Intention of Online Shoppers with Python

Customer Purchase Intention Prediction Python Machine Learning

Online shopping has become a part of our daily lives, and online stores are continually seeking to improve their sales. One way to achieve this is by using machine learning to predict customers’ purchase intentions. This innovative process can help businesses understand their customers’ behavior and tailor their marketing strategies accordingly. In this article, we … Read more

Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?

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Correlation analysis is a powerful tool in financial market analysis, helping investors to better understand the interdependence of different assets. But what happens when an unprecedented global pandemic like COVID-19 shakes up the market? In this tutorial, we will show you how to create a correlation matrix in Python that will help you visualize the … Read more

Stock Market Prediction – Adjusting Time Series Prediction Intervals in Python

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Get ready to level up your time-series forecasting game! In this tutorial, we’re going to take things up a notch by showing you how to adjust prediction intervals using Keras recurrent neural networks and Python. Now, you may remember our previous article on stock market forecasting where we made a forecast for the S&P500 stock … Read more

Stock Market Prediction using Univariate Recurrent Neural Networks (RNN) with Python

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Financial analysts have long been fascinated by the prospect of predicting the prices of financial assets. In recent years, there has been increasing interest in using machine learning and deep learning techniques to generate predictions, in addition to traditional methods such as technical and fundamental analysis. Python libraries like Keras and Scikit-Learn make it relatively … Read more

Flight Delay Prediction using Azure Machine Learning

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If you travel a lot, you’ve probably already experienced this – you’re in a hurry on your way to the airport trying to catch a flight, only to find out that your flight is delayed. Wasn’t it great to know when a flight will be delayed in advance? We can use past flight delay data … Read more