Build ranking system & stock market pro chatbot using langchain, openai and hugging face model, TensorFlow & vector db
What you will learn
Overview of terms used in this course
Overview of building ranking system using tensor flow, hugging face transformer, pipecone vector db, and neural network
Ranking system POC code walk through
Overview of building a market pro chatbot using langchain, openAI, and in memory vector db
Market pro chatbot code walk through
Description
Learn how to create a sophisticated ranking system and a cutting-edge stock market professional chatbot by leveraging the power of advanced AIML tooling and frameworks. In this comprehensive course, you will gain hands-on experience with a variety of state-of-the-art technologies and techniques to build intelligent systems that excel in ranking and stock market analysis.
We will begin by exploring LangChain, a powerful language modeling framework that enables the creation of intelligent conversational agents. You will dive deep into its capabilities and learn how to harness its potential to build robust and context-aware chatbots.
Next, we will delve into the world of machine learning with Tensorflow. Through practical exercises, you will acquire a solid understanding of neural networks and their application in training models for accurate predictions and decision-making in the stock market domain.
To further enhance your AI toolkit, we will introduce you to OpenAI, an industry-leading platform that offers a plethora of cutting-edge machine learning models and APIs. You will explore its vast capabilities and leverage its powerful algorithms to enhance your chatbot’s natural language processing capabilities.
Additionally, we will explore the Hugging Face Transformer library, which provides a comprehensive suite of pre-trained models for a wide range of natural language processing tasks. You will learn how to fine-tune these models to create a highly intelligent and contextually aware chatbot.
Furthermore, you will gain expertise in working with Pipecone Vector DB, an efficient and scalable database specifically designed for managing large volumes of vectors. You will learn how to store and query vector-based data, such as embeddings generated by your chatbot, effectively.
Lastly, you will explore InMemory Vector DB, a fast and memory-efficient database solution that enables real-time data access and manipulation. You will learn how to leverage its capabilities to improve the performance of your ranking system and stock market chatbot.
By the end of this course, you will have acquired the skills and knowledge needed to build sophisticated ranking systems and stock market professional chatbots, empowering you to make informed decisions and succeed in the rapidly evolving world of artificial intelligence and finance.
Content
