Text classification is one of the most important tasks in Natural Language Processing. It is the process of classifying text strings or documents into different categories, depending upon the contents of the strings. Text classification has a variety of applications, such as detecting user sentiment from a tweet, classifying
A typical machine learning process involves training different models on the dataset and selecting the one with best performance. However, evaluating the performance of algorithm is not always a straight forward task. There are several factors that can help you determine which algorithm performance best. One such factor is
Hierarchical clustering is a type of unsupervised machine learning algorithm used to cluster unlabeled data points. Like K-means clustering, hierarchical clustering also groups together the data points with similar characteristics. In some cases the result of hierarchical and K-Means clustering can be similar. Before implementing hierarchical clustering using Scikit-Learn, let's
When studying Probability & Statistics, one of the first and most important theorems students learn is the Bayes' Theorem. This theorem is the foundation of deductive reasoning, which focuses on determining the probability of an event occurring based on prior knowledge of conditions that might be related to the event.
Random forest is a type of supervised machine learning algorithm based on ensemble learning. Ensemble learning is a type of learning where you join different types of algorithms or same algorithm multiple times to form a more powerful prediction model. The random forest algorithm combines multiple algorithm of the same
