Feb 15 2023 The Complete Openai And Gpt Course - Build A Q&A Chatbot BaDshaH LEARNING / e-learning - Tutorials 09:19 0 Published 2/2023MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 2.05 GB | Duration: 5h 15mMaster OpenAI's GPT, Semantic Search, Embeddings, and Q&A to build a Financial Assistant. Beginner friendly.What you'll learnThe foundations of GPT and generative text - Large Language Models (LLM), Prompt EngineeringReceiver Augmented Generation (RAG) for Question Answering - its use cases and challenges, and real world implementationFinetuning GPT models and their best practices, when and when not to fine tune.Best practice strategies for troubleshooting issues with OpenAI APIsSemantic Search - theory and ImplementationVector databases, Pinecone - how they work, code samplesHow to choose the right GPT model for completion and classification tasksUnderstand how to use OpenAI's APIs and their production best practicesTackling the LLM hallucination problem - what the problem is, and specific strategies to mitigate it.RequirementsPrior exposure to Python and Pandas. You don't need to be an experienced Python and Pandas developer, but the ability to follow along and understand syntax is needed.Github and Google accounts (free)DescriptionNote: This course assumes that you have gotten the basics of Python and Pandas down. You don't need to be an experienced Python and Pandas developer, but the ability to follow along and understand syntax is needed.Take your AI development skills to the next level with this course!In this course, you will learn how to build an AI assistant powered by OpenAI's GPT technology, HuggingFace, and Streamlit. In addition, you will learn the foundational concepts of GPT and generative AI, such as Large Language Models, Prompt Engineering, Semantic Search, Finetuning, and more. You will also understand how to use OpenAI's APIs and their best practices, with real world code samples.Unlike other courses, you will learn by doing. You will start with a blank app, and add features one at a time. Before adding a new feature, you will learn just enough theory to confidently build your app.You will get all the code samples, including Google colab notebooks, and access to the Q&A forum if you get stuck. You don't need a powerful PC or Mac that has GPUs to take this course. By the end of the course, you will be able to deploy and create your first app using OpenAI's technology, and be confident about the theoretical knowledge behind this technology. So sign up today and start building your AI powered app!What you will learn:Creating an AI chatbot with StreamlitIntentClassifiers - what they are, how to build it.Prompt Engineering: different ways of crafting the perfect promptHow to evaluate and choose the best promptThe concept of word embeddingsHow to use word embeddings to quantify semantic similarityHow to use a vector database to store word embeddingsHow to create a search engine that searches based on word embeddingsHow to perform entity resolution for documentsSentiment extraction using GPTHow to clean a finance dataset for use in a semantic searchHow to embed finance documents and upload them to a vector databaseHow to use a language model to generate answers to questionshow to use fine-tuning to ensure the language model does not hallucinateHow to deploy a Q&A bot and a custom action system.OverviewSection 1: IntroductionLecture 1 IntroductionLecture 2 Course Logistics and Important AnnouncementsLecture 3 What We Are Building & Problem StatementLecture 4 FAQLecture 5 Important DisclaimersSection 2: Project 0: Create a ChatGPT Clone with Python and StreamlitLecture 6 Course SetupLecture 7 Course Project SolutionsLecture 8 Building a ChatGPT Clone in 50 lines of CodeLecture 9 Integrating OpenAISection 3: GPT3, Prompt Engineering, and LLMsLecture 10 ChatGPT, GPT3, InstructGPT - How They WorkLecture 11 Prompt Engineering and Advanced GPT ParametersLecture 12 Why GPT Disrupted AI IndustrySection 4: Project 1: Intent ClassifierLecture 13 IntentClassifier - What It is, Why It's ImportantLecture 14 Prompts for Classification Problems (Notebook)Lecture 15 Evaluation GPT3.5 for Classification (Notebook)Lecture 16 Integrate Intent Classifier into the AppSection 5: Limits of GPT - What It Can't DoLecture 17 Limitations of GPT - Knowledge Cutoff, Data Gaps, Token LimitsLecture 18 Limits of GPT - Reasoning, Chain of Thought PromptingSection 6: Project 2: Semantic Search and RetrieversLecture 19 Semantic Search Based RetrievalLecture 20 Word and Sentence Embeddings (Notebook)Lecture 21 Semantic Search (Notebook)Lecture 22 Vector Databases, Pinecone, Nearest Neighbor SearchLecture 23 Integrating News Article Retriever into AppSection 7: Project 3: Retriever Augmented Question Answering and Fine TuninngLecture 24 Question Answering with GPT, and Finetuning GPT ModelsLecture 25 Question Answering, Strategies for Handling Hallucinations (Notebook)Lecture 26 Question Answering and Finetuning GPT (Notebook)Lecture 27 Generative Labeling, Finetuning GPT, Model Evaluation (Notebook)Lecture 28 App IntegrationSection 8: Project 4: Summarization, External System IntegrationLecture 29 Document Summarization with GPTLecture 30 Summarization with GPT (Notebook)Lecture 31 Adding Real Time Financial Charts (Notebook)Lecture 32 App IntegrationLecture 33 DeploymentPython developers with some Pandas experience who are eager to build their first AI app using GPT libraryHomepagehttps://www.udemy.com/course/the-complete-openai-and-gpt-course-build-a-qa-chatbot/Download From Rapidgatorhttps://rapidgator.net/file/1fbfffd603f4c50ef940f031588ce4b1https://rapidgator.net/file/b9be0daae2f4517eb7c65122429e422dhttps://rapidgator.net/file/201a3126eaebd81be5993bf187ff32c5Download From 1DLhttps://1dl.net/35nfn94x6akahttps://1dl.net/8ffcca6zdj5chttps://1dl.net/t3ezqbz64balTo Support My Work Buy Premium From My Links. Published 2/2023MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 2.05 GB | Duration: 5h 15mMaster OpenAI's GPT, Semantic Search, Embeddings, and Q&A to build a Financial Assistant. Beginner friendly.What you'll learnThe foundations of GPT and generative text - Large Language Models (LLM), Prompt EngineeringReceiver Augmented Generation (RAG) for Question Answering - its use cases and challenges, and real world implementationFinetuning GPT models and their best practices, when and when not to fine tune.Best practice strategies for troubleshooting issues with OpenAI APIsSemantic Search - theory and ImplementationVector databases, Pinecone - how they work, code samplesHow to choose the right GPT model for completion and classification tasksUnderstand how to use OpenAI's APIs and their production best practicesTackling the LLM hallucination problem - what the problem is, and specific strategies to mitigate it.RequirementsPrior exposure to Python and Pandas. You don't need to be an experienced Python and Pandas developer, but the ability to follow along and understand syntax is needed.Github and Google accounts (free)DescriptionNote: This course assumes that you have gotten the basics of Python and Pandas down. You don't need to be an experienced Python and Pandas developer, but the ability to follow along and understand syntax is needed.Take your AI development skills to the next level with this course!In this course, you will learn how to build an AI assistant powered by OpenAI's GPT technology, HuggingFace, and Streamlit. In addition, you will learn the foundational concepts of GPT and generative AI, such as Large Language Models, Prompt Engineering, Semantic Search, Finetuning, and more. You will also understand how to use OpenAI's APIs and their best practices, with real world code samples.Unlike other courses, you will learn by doing. You will start with a blank app, and add features one at a time. Before adding a new feature, you will learn just enough theory to confidently build your app.You will get all the code samples, including Google colab notebooks, and access to the Q&A forum if you get stuck. You don't need a powerful PC or Mac that has GPUs to take this course. By the end of the course, you will be able to deploy and create your first app using OpenAI's technology, and be confident about the theoretical knowledge behind this technology. So sign up today and start building your AI powered app!What you will learn:Creating an AI chatbot with StreamlitIntentClassifiers - what they are, how to build it.Prompt Engineering: different ways of crafting the perfect promptHow to evaluate and choose the best promptThe concept of word embeddingsHow to use word embeddings to quantify semantic similarityHow to use a vector database to store word embeddingsHow to create a search engine that searches based on word embeddingsHow to perform entity resolution for documentsSentiment extraction using GPTHow to clean a finance dataset for use in a semantic searchHow to embed finance documents and upload them to a vector databaseHow to use a language model to generate answers to questionshow to use fine-tuning to ensure the language model does not hallucinateHow to deploy a Q&A bot and a custom action system.OverviewSection 1: IntroductionLecture 1 IntroductionLecture 2 Course Logistics and Important AnnouncementsLecture 3 What We Are Building & Problem StatementLecture 4 FAQLecture 5 Important DisclaimersSection 2: Project 0: Create a ChatGPT Clone with Python and StreamlitLecture 6 Course SetupLecture 7 Course Project SolutionsLecture 8 Building a ChatGPT Clone in 50 lines of CodeLecture 9 Integrating OpenAISection 3: GPT3, Prompt Engineering, and LLMsLecture 10 ChatGPT, GPT3, InstructGPT - How They WorkLecture 11 Prompt Engineering and Advanced GPT ParametersLecture 12 Why GPT Disrupted AI IndustrySection 4: Project 1: Intent ClassifierLecture 13 IntentClassifier - What It is, Why It's ImportantLecture 14 Prompts for Classification Problems (Notebook)Lecture 15 Evaluation GPT3.5 for Classification (Notebook)Lecture 16 Integrate Intent Classifier into the AppSection 5: Limits of GPT - What It Can't DoLecture 17 Limitations of GPT - Knowledge Cutoff, Data Gaps, Token LimitsLecture 18 Limits of GPT - Reasoning, Chain of Thought PromptingSection 6: Project 2: Semantic Search and RetrieversLecture 19 Semantic Search Based RetrievalLecture 20 Word and Sentence Embeddings (Notebook)Lecture 21 Semantic Search (Notebook)Lecture 22 Vector Databases, Pinecone, Nearest Neighbor SearchLecture 23 Integrating News Article Retriever into AppSection 7: Project 3: Retriever Augmented Question Answering and Fine TuninngLecture 24 Question Answering with GPT, and Finetuning GPT ModelsLecture 25 Question Answering, Strategies for Handling Hallucinations (Notebook)Lecture 26 Question Answering and Finetuning GPT (Notebook)Lecture 27 Generative Labeling, Finetuning GPT, Model Evaluation (Notebook)Lecture 28 App IntegrationSection 8: Project 4: Summarization, External System IntegrationLecture 29 Document Summarization with GPTLecture 30 Summarization with GPT (Notebook)Lecture 31 Adding Real Time Financial Charts (Notebook)Lecture 32 App IntegrationLecture 33 DeploymentPython developers with some Pandas experience who are eager to build their first AI app using GPT libraryHomepagehttps://www.udemy.com/course/the-complete-openai-and-gpt-course-build-a-qa-chatbot/Download From Rapidgatorhttps://rapidgator.net/file/1fbfffd603f4c50ef940f031588ce4b1https://rapidgator.net/file/b9be0daae2f4517eb7c65122429e422dhttps://rapidgator.net/file/201a3126eaebd81be5993bf187ff32c5Download From 1DLhttps://1dl.net/35nfn94x6akahttps://1dl.net/8ffcca6zdj5chttps://1dl.net/t3ezqbz64balTo Support My Work Buy Premium From My Links. Related News Openai, Gpt, Chatgpt And Dall-E MasterclassTutorials On Python & Data Science - Python + Data ScienceChatgpt Masterclass: Smart Tips & Chatgpt Insights & FutureAi: Unleashing Gpt-3'S Potential For Productivity.Certified Solidworks Professional Cswp Prep Course 2023 Comments (0)Add comment Submit NEWEST RELEASES 20.05: TurboCollage 7.3.2.0 Home / Advanced / Professional Portable 20.05: Glary Utilities Pro 6.10.0.14 Multilingual Portable 20.05: PhotoGlory 6.00 Portable 20.05: Tone Empire RES-Q v1.3 19.05: Plugin Alliance Bx Crispytuner v1.1.0 19.05: Reportizer 6.5.5.112 Multilingual 19.05: Exportizer Enterprise 9.3.1.121 Multilingual 19.05: Runtime GetDataBack Pro 5.70 19.05: Plugin Alliance TBTECH Cenozoix Compressor v1.1.0 19.05: Watchdog Anti-Virus 1.6.746 Recommended Filehosts Freinds Site