💡 Week 6: Embeddings and Vector Stores/Databases Welcome to Week 6 of the ML Study Jam series! 🌟 This week, we’ll delve into Embeddings and explore the role of Vector Stores/Databases in modern AI applications. This foundational session is designed to help you understand and apply concepts crucial for building intelligent and context-aware systems.
6 RSVP'd
📅 Date: 23 March
⏰ Time: 4PM
🌐 Location: Virtual
In Week 6: Embeddings and Vector Stores/Databases:
✔️ An introduction to embeddings and their importance in representing complex data
✔️ Insights into vector databases and search algorithms used in real-world AI applications
✔️ A roadmap for continuing self-paced study and experimenting with tools
After the session, participants will continue with self-paced study to deepen their understanding and practice implementing embeddings and vector stores in projects.
1️⃣ Completion of Week 5’s Foundational Models & Prompt Engineering 📚
2️⃣ Access to an embedding generation tool (e.g., Hugging Face, OpenAI, or TensorFlow) 🌐
3️⃣ A readiness to experiment with vector database platforms ✅
This session and self-paced study will empower participants to build systems capable of understanding, organizing, and retrieving data effectively—essential for advanced AI applications.
This program unfolds across multiple weeks, offering foundational insights and advanced explorations into machine learning and generative AI.
ML Study Jam Weekly Plan:
1️⃣ Week 1: Intro to Machine Learning
2️⃣ Week 2: Intermediate Machine Learning
3️⃣ Week 3: Intro to Deep Learning
4️⃣ Week 4: Intro to AI Ethics
5️⃣ Week 5: Foundational Models & Prompt Engineering
6️⃣ Week 6: Embeddings and Vector Stores/Databases
7️⃣ Week 7: Generative AI Agents
8️⃣ Week 8: Domain-Specific LLMs
9️⃣ Week 9: MLOps for Generative AI
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