I come from a Non-IT background and have found myself delving into the fascinating world of programming and cutting-edge technologies. Thanks to the invaluable guidance and tutorials by Dhawal Patel, I've been able to not only grasp but also teach Python, Java, and delve into complex domains like Machine Learning. Currently, my focus lies in research within bioinformatics, where I utilize deep learning and NLP techniques. I owe a tremendous debt of gratitude to Dhawal Sir, whose teachings have been instrumental in shaping my journey. Without his insightful tutorials and unwavering support, I wouldn't have dared to dream of venturing into these domains. My deepest respect and appreciation go out to Dhawal Sir for his mentorship and guidance.
so far the best explanantion I heard on LLM. Thanks for all your hardwork in these videos.
00:01 Overview of Generative AI 02:31 Evolution from statistical ML to deep learning with neural networks 07:30 Transformers have led to a variety of powerful AI models. 09:59 Buddy is a stochastic parrot with mimicking ability and statistics-based predictions. 14:58 Understand Vector database and semantic search 17:21 Word to numeric representation using word embeddings 21:29 Retrieval Augmented Generation (RAG) allows fine-tuning or building AI models on specific data sets. 23:48 Using GPT-3 for querying data sources 28:24 To work with Gen AI, you need models, cloud services, and frameworks. 30:27 LLM based application using OpenAI API 34:36 Creating separate keys for different projects and managing them securely 36:55 Using LLM to generate creative restaurant names based on cuisine preferences. 41:33 Implementing Simple Sequential Chain concept in Gen AI Course 44:00 Using sequential chains to get both restaurant name and menu items in Gen AI Course 48:44 Setting up Streamlit for application development 51:15 Using response data to display restaurant name and menu items in UI 56:13 Practice coding while watching the video 58:22 Gen AI has a reasoning component for answering questions beyond its knowledge 1:02:48 Using Gen AI to retrieve information about Elon Musk's age in 2023 1:05:11 Initializing environment variables and using AI tools in an agent. 1:09:49 Using conversation chain to optimize cost and memory 1:12:15 Optimize OpenAI token cost by limiting conversational buffer memory 1:16:39 Research analysts provide detailed stock research for companies like Tata Motors and Reliance. 1:18:42 Importance of building a specialized tool over using Chat GPT 1:22:52 Using semantic search for finding relevant text chunks 1:24:56 Utilizing Vector databases for faster search and retrieval 1:29:05 Installing and loading Lang chain library in Jupyter notebook 1:31:39 Providing explanation about the movies.CSV file contents. 1:36:25 Text splitting and merging for efficient processing 1:38:35 Using Lang chain provides a simple API for text splitting. 1:43:22 Text splitting process using separators and size constraints 1:46:05 Gen AI Course explains recursive text splitter and merging for chunk optimization 1:50:23 Demonstration of using libraries to convert text into vectors 1:52:42 Using meditation and yoga to improve mental health with vector representation 1:57:30 Gen AI performs semantic search to provide results based on context, not just keywords 1:59:42 Retrieval QA with Sources Chain 2:04:06 Creating open API embeddings for document retrieval 2:06:39 Using a Vector database and creating a retrieval chain for text analysis. 2:11:06 Assembling the final project with pre-built individual pieces 2:13:10 Loading environment variables and creating basic UI in Gen AI module 2:18:20 Saving data in memory and displaying progress 2:20:46 Setting up Vector database and creating retrieval QA chain in Python 2:25:43 Automated news research tool for equity analysts 2:27:53 Utilizing vector databases for storing embeddings in large projects 2:32:07 Utilizing Google Palm and SQL Database Chain in Lang Chain Framework 2:34:10 Introduction to Vector Database and Google Palm for AI applications 2:38:14 Explaining the t-shirt records and database setup 2:40:45 Setting up a SQL database object with URI 2:45:40 Understanding the importance of correct database mapping for accurate results 2:48:17 Learning to run and manage queries in DB Chain 2:53:13 Summing of stock quantities for white color t-shirts 2:55:42 Storing data into arrays and using Hugging Face embedding for generating embeddings 3:00:34 Vector store converts input questions into embeddings for similarity matching. 3:02:52 Import SQL prompt template to generate queries. 3:07:42 Enhanced querying functionality with additional parameters 3:10:00 Creating a streamlit UI with few lines of code 3:14:54 Creating a main function in Python and running SQL queries in a database chain 3:17:27 Using Streamlet to ask and answer questions efficiently Crafted by Merlin AI.
sir your way of explaining things with examples is mindblowing , never seen anyone teaching like this before , absolutely amazed . thank you for this course 🙏🙏
This is an extremely informative video for GenAI, learning about LLMs, building connections with Python and creating our projects. Dhaval - you are a great teacher!
I have 10+ years' experience in the fintech domain (non-technical background), but this session was so easy to understand. Keep up the great work, Dhaval.
The finest explanation of LLM I've heard so far. I appreciate all of your efforts in making these videos. I am started learning the Gen AI. Thanks😀
Dhaval sir, except for being a Dosa lover, I have nothin in common with you. THis is a great intelligently compiled video that keeps engaged, educates and makes a much values consultant after. thank you very much
This is the best course video I have watched on youtube on GenAI. Amazing work.
Wow - you did such an awesome job producing this video! superb explanations and video production. Thanks for making this
The way you explain everything thing more effectively is really good
What a teacher!. Sir, your videos is so so so nice, that i'm not getting bored at all, even though i'm learning this technology for the very first time. sir, thankyou so much for creating such beautiful and amazing content.... lots of good wishes for you from the bottom of my heart!
OpenAI has stopped issuing few credits. You have two options (1) By spending less than 5$ on openai API, you can complete this project. You will learn a valuable skill by spending money that may be less than what you spend in a restaurant for a dinner. (2) Use LLama 3 etc open source model in groq.com or do the project using google gamma or palm models (the second project has relevant information on that). To learn AI concepts in a simplified and practical manner check our course "AI for everyone": https://codebasics.io/courses/ai-for-everyone-your-first-step-towards-ai
One of the best content on YouTube ever found.... I have an interview and your video provided all knowledge needed for a fresher. You made my day sir,, huge respect to you 🫡
Watched just first 20 minutes of this video. The sequencing, content and flow is very good. Watched few other video on GenAI. This is the far best for me. Thank you for this wonderful content!
Thanks for this detailed video sir.. this was my first video watching on GenAI, this video has given initial confidence about basic info already…Tks a ton 🙏
Great explaining. Will rewatch this.
you are simply killing it man, thanks so much quality
Thanks for clarifying the fundamentals of GenAI .. excellent tutorial and really helps me to understand the basics and kind of directions as well how to move further and get into deeper and deeper of GenAI .
@codebasics