Tag: module-56
This article explores a robust, adaptive framework for incremental learning for sentiment analysis using the SGD Classifier.
coding, module-56, python-coding, sentiment analysis applicationFeature engineering is used after the data preparation step which involves handling missing values, removing duplicates, detecting outliers, and encoding categorical variables.
feature engineering, module-56, sentiment analysis applicationIncremental learning also known as continuous learning is a crucial paradigm in machine learning that enables models to adapt over time. The world is generating an enormous amount of data, often in continuous streams, which makes traditional data analysis methods difficult.
coding, module-56, python-coding, sentiment analysis applicationRAPIDS cuDF provides a pandas-like interface but is designed to leverage NVIDIA GPUs for accelerated data processing using CUDA.
coding, goal-2, milestone-546, module-56, python-coding, sentiment analysis applicationThe overwhelming volume of social media data has created complex challenges for digital governance and policy-making, particularly in identifying and addressing social bias embedded in online discourse.
basics of sentiment analysis, module-56, python-codingFine-tuning a pre-trained model involves taking a model already trained on a large, general dataset and adapting it to perform well on a smaller, specific task dataset. Transformers is a library of several pre-trained large language models (LLMs) available as open source for training and inference (Hugging Face, n.d.-b). Transformer models are language models that […]
basics of sentiment analysis, module-56, python-codingMachine learning is a transformative branch of artificial intelligence (AI) focused on developing algorithms that enable computers to learn from data (Talwar & Kumar, 2013). Instead of following rigid, predefined rules, machine learning systems improve their performance over time by identifying patterns and relationships in data.
basics of sentiment analysis, module-56, python-coding, regression analysisThe Valence Aware Dictionary and Sentiment Reasoner (VADER) is a lexicon-based sentiment analysis tool that uses a lexicon dictionary to assign predefined sentiment scores.
basics of sentiment analysis, module-56, python-coding