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) …
Tokenization in NLP: A Comprehensive Guide
Hi Folks, In this article we are going to know about NLP and their deep knowledge. this blog is actually a series of NLP concepts.
So let’s get started with the blog/article.
Tokenization is like breaking a sentence into individual …
Creating Your Own PDF Chatbot : LLM
Are you interested in creating your own PDF chatbot but want to have full control over every aspect of the bot? Look no further! In this tutorial, we will guide you through the process of building a PDF chatbot without …
A Comprehensive Guide to Hugging Face Transformers
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 …
Predicting House Prices using Machine Learning: A Step-by-Step Guide
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 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 …