Crash Course 🔥 Master Travel Planning with AI Agents and Web Apps

Описание: In this comprehensive course, you'll learn how to create a sophisticated multi-agent system designed to assist users in planning their travel experiences using advanced AI agents and powerful large language models. We will guide you through the creation of three essential agents: a Weather Agent that analyzes real-time weather data, a Hotel Agent dedicated to finding the best accommodations, and an Itinerary Agent that generates personalized travel plans. You'll also discover how to develop a user-friendly web interface using Streamlit, ensuring seamless interaction with our agents. Additionally, we will delve into asynchronous programming techniques to optimize the performance of our agents, making them operate efficiently. To top it off, you will containerize the entire application using Docker for smooth and hassle-free deployment, ensuring your travel planning tool is robust and reliable.
GitHub Repository: https://github.com/martinyanev94/trav...


0:00:00 - 0 Introduction to the Course
0:00:45 - 1 Representing Text For Artificial Intelligence
0:13:20 - 2 Word Embeddings And Their Applications
0:26:04 - 3 Word2Vec Explanation
0:40:37 - 4 Optimizing Word Embeddings
0:51:25 - 5 Text Representation Techniques
1:00:06 - 6 Deep Learning Models For Text Analysis
1:09:31 - 7 Embedding Vectors For Word Representation
1:17:11 - 8 Contextual Word Similarity Through Neural Networks
1:26:02 - 9 Recurrent Neural Networks For Text Processing
1:37:18 - 10 Sentiment Analysis Using Deep Learning
1:46:54 - 11 Deep Learning Models For Text Classification
1:56:50 - 12 Word Embeddings And Contextual Similarity
2:07:34 - 13 Text Normalization Techniques
2:18:40 - 14 Advanced Word Embeddings
2:31:05 - 15 Advanced Techniques For Sentiment Analysis
2:40:42 - 16 Embedding Applications In Natural Language Processing
2:50:03 - 17 Understanding Word Embedding Techniques
2:58:14 - 18 Implementing Neural Networks For Sentiment Analysis
3:07:11 - 19 Bag-Of-Words Algorithm
3:16:42 - 20 Deep Learning Models For Text Classification
3:27:11 - 21 Advanced Text Processing Techniques
3:36:08 - 22 Applications Of Embedding In Natural Language Processing
3:45:37 - 23 Word Embeddings Introduction
3:55:39 - 24 Contextual Word Representations
4:04:34 - 25 Advanced Techniques For Natural Language Processing
4:13:38 - 26 Embedding Representation Methods In Deep Learning
4:22:59 - 27 Advanced Natural Language Processing Techniques
4:32:14 - 28 Techniques For Applying Word Embeddings In Sentiment Analysis
4:43:16 - 29 Analyzing Text Data With Deep Learning
4:53:59 - 30 Embedding Application And Representation
5:01:51 - 31 Embedding Process And Word2Vec Framework


Business contact: [email protected]