Driven by an intense desire to understand data and fueled by the opportunities presented during the COVID-19 pandemic, I enthusiastically ventured into the vast world of Python, Machine Learning, and Deep Learning. Through online courses and extensive self-learning, I immersed myself in these areas. This led me to pursue a Master's degree in Data Science. To enhance my skills, I actively engaged in data annotation while working at Biz-Tech Analytics during my college years. This experience deepened my understanding and solidified my commitment to this field.
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Oct 10, 2024 · 3 min read · An LLM (Large Language Model) is a neural network designed to understand, generate, and respond to human-like text. These models are deep neural networks trained on massive amounts of text data, sometimes encompassing large portions of publicly avail...
Join discussionOct 8, 2024 · 2 min read · Once you’ve created a dataset, you want to explore the values inside. Exploring very large datasets can be difficult, as even simple operations can be expensive, both in terms of computational resources and time. The same sampling principle applies t...
Join discussionAug 16, 2024 · 2 min read · There is nothing new about this. People have been seeking patterns in data since human life began. Hunters seek patterns in animal migration behavior, farmers seek patterns in crop growth, politicians seek patterns in voter opinion, and lovers seek p...
Join discussionAug 13, 2024 · 2 min read · Understanding the roles of train, validation, and test data is essential for building robust matching learning models. Properly splitting and using the datasets ensures that the model generalizes well to new data, making it reliable and effective in ...
Join discussionJul 22, 2024 · 2 min read · Introduction to In-House Data Labeling Data annotation, often called data labeling, is a cornerstone of the AI integration pipeline. It acts as the bridge between the raw data and a functional ML model. The annotators or automated tools add labels or...
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