In this repository, I delve into the world of data visualization, exploring various techniques and tools to effectively communicate insights from data. Additionally, I embark on a learning journey to understand algorithms and data structures, leveraging the power of Large Language Models (LLMs) to bridge the gap between text and image data.
Exploratory Data Analysis with Matplotlib and Seaborn
Dive into the basics of data visualization using popular Python libraries Matplotlib and Seaborn. Explore techniques for creating insightful plots and charts to gain valuable insights from raw data.
Interactive Data Visualization with Plotly
Discover the interactive capabilities of Plotly for creating dynamic and engaging visualizations. Learn how to build interactive dashboards and explore complex datasets with ease.
Introduction to LLMs for Natural Language Processing
Explore the fundamentals of Large Language Models (LLMs) and their applications in natural language processing tasks. Dive into pre-trained models and learn how to leverage their power for text analysis.
Text-to-Image Generation with LLMs
Delve into cutting-edge techniques for generating images from text descriptions using LLMs. Explore the intersection of language and vision and witness the fascinating capabilities of these models.
Algorithmic Explorations: Data Structures and Beyond
Embark on a journey through fundamental algorithms and data structures essential for efficient problem-solving. Gain a deeper understanding of algorithmic concepts and their practical implementations.
LLMs for Image Captioning
Witness the synergy between language and image processing as LLMs generate descriptive captions for images. Explore state-of-the-art approaches for bridging the semantic gap between text and images.
Quantization Techniques for LLMs
Explore techniques for compressing and optimizing Large Language Models (LLMs) for efficient deployment and execution. Learn about quantization methods to reduce model size and improve inference speed.
Cloud Quantum Computing for LLMs
Investigate the potential of cloud quantum computing in enhancing the capabilities of Large Language Models (LLMs). Explore the integration of quantum computing techniques, such as Qubernetes, for advancing LLMs research and development.
Through these notebooks, I aim to not only enhance my understanding of data visualization and algorithmic concepts but also explore the exciting intersection of language models, data structures, and quantum computing. Each notebook serves as a stepping stone towards unlocking the full potential of LLMs and their applications in various domains.