AI-powered automation is incredible, but it can also be expensive—especially when using LLMs for every little task. While building a voice-controlled automation system, I realized that extracting parameters from user commands was driving up LLM costs unnecessarily.
Automate customer feedback with AI! Feedbacker classifies reviews, generates responses, and emails customers—boosting engagement while ensuring ethical AI use.
Delve into the intricacies of Convolutional Neural Networks (CNNs), the powerhouse behind modern computer vision tasks. Learn how CNNs detect features, optimize patterns, and classify images efficiently, making them indispensable in AI applications.
Lecture 22 of the Innoquest Cohort-1 training was a masterclass on LLMs: their mechanics, fine-tuning, and real-world applications. These insights are driving my multi-category reviews classifier project forward. Read more about my journey and takeaways.
In this session of Innoquest Cohort-1, I gained invaluable insights into NLP preprocessing techniques, embeddings, and how to leverage CNNs for text classification. These hands-on lessons not only sharpened my skills but also laid the foundation for applying these concepts to real-world AI projects.
Imagine a world where your next favorite movie finds you! 🎥✨ My personalized Movies Recommendation System leverages AI to analyze genres, actors, and user preferences, delivering tailored suggestions that redefine movie discovery. 🚀"
How good are your clusters? The Silhouette Score helps you measure cohesion and separation to evaluate clustering quality. 📊 Dive into practical tips, formulas, and insights to optimize models like K-Means or DB-SCAN! 🚀
Building an ANN for CIFAR-10 classification during Innoquest Cohort-1 AI/ML Training was a hands-on opportunity to master neural network design. While ANNs are suboptimal for image data, this assignment strengthened my skills in PyTorch, architecture design, and data preparation.
Unlock the power of density-based clustering with DB-SCAN! 🧠 This algorithm excels at identifying irregular clusters and outliers, making it a game-changer for complex datasets.
Explore Hierarchical Clustering! 📊 Learn its types, linkage methods, advantages, disadvantages, when to use, Python code example and more.
