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Generative AI with LangChain : Build Large Language Model (LLM) Apps with Python, ChatGPT, and Other LLMs. by Auffarth, Ben

Table of Contents: “…-- What are tools? -- How does LangChain work? -- Comparing LangChain with other frameworks -- Summary -- Questions -- Chapter 3: Getting Started with LangChain -- How to set up the dependencies for this book -- pip -- Poetry -- Conda -- Docker -- Exploring API model integrations -- Fake LLM -- OpenAI -- Hugging Face -- Google Cloud Platform -- Jina AI -- Replicate -- Others -- Azure -- Anthropic -- Exploring local models -- Hugging Face Transformers -- llama.cpp -- GPT4All -- Building an application for customer service -- Summary -- Questions -- Chapter 4: Building Capable Assistants -- Mitigating hallucinations through fact-checking -- Summarizing information -- Basic prompting -- Prompt templates -- Chain of density -- Map-Reduce pipelines -- Monitoring token usage -- Extracting information from documents -- Answering questions with tools -- Information retrieval with tools -- Building a visual interface -- Exploring reasoning strategies -- Summary -- Questions -- Chapter 5: Building a Chatbot like ChatGPT -- What is a chatbot? …”
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Soft Computing: Theories and Applications Proceedings of SoCTA 2016, Volume 1 /

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Deep Learning with TensorFlow and Keras - 3rd Edition : Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models. by Kapoor, Amita

Table of Contents: “…-- Introduction to neural networks -- Perceptron -- Our first example of TensorFlow code -- Multi-layer perceptron: our first example of a network -- Problems in training the perceptron and solution -- Activation function: sigmoid -- Activation function: tanh -- Activation function: ReLU -- Two additional activation functions: ELU and Leaky ReLU -- Activation functions -- In short: what are neural networks after all? …”
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