14,377円 Language ability is a unique human trait, and it is indispensable throughout the human life cycle. Blockchain on the other hand, is an innovation that will transform production relationships, change collaboration models and distribution of benefits between people. Language and blockchain seem to ...

1,657円 The dataset used in this project consists of student achievement in secondary education of two Portuguese schools. The data attributes include student grades, demographic, social and school-related features) and it was collected by using school reports and questionnaires. Two datasets are provide...

1,989円 In this book, we explored a code implementation for sentiment analysis using machine learning models, including XGBoost, LightGBM, and LSTM. The code aimed to build, train, and evaluate these models on Twitter data to classify sentiments. Throughout the project, we gained insights into the key st...

1,657円 In this project focused on sentiment analysis of hotel reviews, the journey commenced with a thorough exploration of the dataset. The dataset comprised various features such as review text, ratings, and user demographics. Distribution analysis of these features revealed insightful patterns, allow...

1,657円 The project "Bank Loan Status Classification and Prediction Using Machine Learning with Python GUI" begins with data exploration, where the dataset containing information about bank loan applicants is analyzed. The data is examined to understand its structure, check for missing values, and gain i...

1,989円 In this project, we embarked on a comprehensive journey of exploring the dataset and conducting analysis and predictions in the context of online retail. We began by examining the dataset and performing RFM (Recency, Frequency, Monetary Value) analysis, which allowed us to gain valuable insights ...

1,657円 In the context of sentiment analysis and opinion mining, this project began with dataset exploration. The dataset, comprising user reviews or social media posts, was examined to understand the sentiment labels' distribution. This analysis provided insights into the prevalence of positive or negat...

1,657円 This is a captivating book that delves into the intricacies of building a robust system for emotion detection in textual data. Throughout this immersive exploration, readers are introduced to the methodologies, challenges, and breakthroughs in accurately discerning the emotional context of text. ...

1,657円 The dataset used in this project consists of the growth of supermarkets with high market competitions in most populated cities. The dataset is one of the historical sales of supermarket company which has recorded in 3 different branches for 3 months data. Predictive data analytics methods are eas...

1,657円 The dataset used in this project has been sourced from the Machine Learning Repository of University of California, Irvine (UC Irvine): Travel Review Ratings Data Set. This dataset is populated by capturing user ratings from Google reviews. Reviews on attractions from 24 categories across Europe ...

1,657円 This project focuses on detecting cyberbullying tweets using both Machine Learning and Deep Learning techniques with a Python GUI implemented using PyQt. The first step involves data exploration, where the dataset is loaded and analyzed to gain insights into its structure and contents. Visualizat...

1,657円 The purpose of this project is to develop a comprehensive Hate Speech Detection and Sentiment Analysis system using both Machine Learning and Deep Learning techniques. The project aims to create a robust and accurate system that can automatically identify hate speech in text data and perform sent...