Artificial Intelligence (AI) agents, powered by advanced algorithms and large language models (LLMs), are rapidly becoming a driving force behind innovation in fields like software development, customer service, and more. These autonomous systems perform …
Sentiment analysis is like teaching a computer to understand feelings – it can tell whether a text expresses happiness, sadness, or something in between. In this step-by-step guide, we’ll learn how to do sentiment analysis with Natural Language Processing (NLP) …
In the vast field of natural language processing (NLP), Hugging Face Transformers has emerged as a go-to library for leveraging the power of pre-trained models. Whether you’re a beginner or an experienced NLP practitioner, this open-source library provides an efficient …
As the real estate market continues to grow, there is an increasing demand for accurate predictions of house prices. With the power of machine learning, it is now possible to predict the price of a house based on its features …
Will see the Importance, why, and when we use Recall and Precision.
Recall is important when you want to minimize the number of false negatives, even if it means increasing the number of false positives. Some examples of situations …
Evaluating the performance of a machine learning model is an important step in the model development process, as it allows us to assess how well the model is able to make predictions on new data. This can be done by …
Model evaluation is the process of assessing the performance of a model on a dataset. This is typically done by splitting the original dataset into training and testing sets and using the testing set to evaluate the model’s performance.
The …
Machine learning is a type of artificial intelligence that allows computer programs to learn from data and improve their performance on a specific task without being explicitly programmed. Building a machine learning model involves selecting a model type, training the …
Dividing customers into groups based on similar functionality or customer segmentation is based on the problem of clustering which means finding clusters in a dataset with the same features.
Customer segmentation can help a business focus on marketing strategies to …
Ordinary Least Squares won’t work well with non-linear data. If you are not sure about the linearity or if you know your data has non-linear relations then this is a giveaway that most likely Ordinary Least Squares …
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