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Feature extraction is a key process in machine learning and computer vision. It involves transforming raw data into a set of measurable and meaningful attributes or characteristics—called features—that can be used for further analysis, such as classification or prediction. The Read More …
Introduction Game theory is a mathematical framework for analyzing strategic interactions among rational decision-makers. It studies how individuals or entities make choices that depend on the actions of others, aiming to predict outcomes in situations of conflict or cooperation. Here’s Read More …
How to connect printer to Wi-Fi ? How to connect the printer to Wi-Fi ? We can connect our printer to Wi-Fi to print over Wi-Fi from our computer. This process takes the following steps. First of all turn on Read More …
What is DALL-E DALL-E (pronounced “Dolly”) is a series of artificial intelligence models developed by OpenAI that can generate original digital images from natural language descriptions, known as “prompts.” The name is a blend of “Dali” (after Salvador Dalí) and Read More …
Generative Artificial Intelligence (AI) Generative AI is a type of artificial intelligence that creates new content, such as text, images, audio, or videos, based on patterns and data it has been trained on. It uses models like large language models Read More …
Why it is necessary to get the idea of overflow? Numbers represented in computer system have always have a specific range. It depends on how many bits your system process. Some systems are 32 bits while other are 64-bits. With the advancement in technology we have now larger bits processing systems. But they have limited range of numbers they can represent. Overflow refers to the condition when the given bits can not represent the given number. It means that number needs more bits for its representation. There is another situation where the number is small enough and not representable according to the given pattern of numbers. This is called underflow.
Ridge Regression Ridge Regression is a type of linear regression that adds a regularization term to the cost function to prevent overfitting, especially when predictors are highly correlated (multicollinearity). It modifies ordinary least squares by including an L2 penalty, which Read More …
Introduction to Bayes Theorem The Naive Bayes algorithm is a simple, probabilistic machine learning method used for classification tasks. It’s based on Bayes’ Theorem, which calculates the probability of an event given prior knowledge. The “naive” part comes from its Read More …
Histogram of Oriented Gradients (HOG) is a feature detection algorithm based on the image’s gradients. It is a classic approach for object detection in an image, e.g., a vehicle in the street, a pedestrian walking in the street, etc. Examples Read More …
The Apriori Algorithm is a classic algorithm used in association rule mining and frequent itemset mining over transactional databases. It is particularly useful in market basket analysis, where the goal is to find relationships between items bought together. Key Concepts Read More …