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 …
when Recall, Precision, Accuracy, and F1 score is Important
Will see the Importance, why, and when we use Recall and Precision.
Recall
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 …
Confusion matrix – Example, Scenario and Code
A confusion matrix is a table that is often used to describe the performance of a classification model (or “classifier”) on a set of data for which the true values are known. It allows you to see how well your …
Evaluating the model performance [Deep Understanding] – Machine Learning
![_Evaluating the model performance [Deep Understanding]](https://www.techjunkgigs.com/wp-content/uploads/2022/12/Evaluating-the-model-performance-Deep-Understanding-300x169.png)
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 …
Machine Learning – Random Forest
Random forests are a powerful machine learning algorithm that can be used for both classification and regression tasks. They are an ensemble learning method, which means they use multiple decision trees to make predictions, and combine the results to improve …
Machine Learning – Model Evaluation
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 – Model Building
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 …
ML – Customer Segmentation
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 …
NLP – Bag of Words
Bag of Words
A bag of words is a particular representation model used to simplify the contents of a selection of text. The bag of words model omits grammar and word order but is interested in the number of occurrences …
NLP – Word segmentation
Word segmentation
This is the act of taking a string of text and deriving word forms from it. Example: A person scans a handwritten document into a computer. The algorithm would be able to analyze the page and recognize that …
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