{"product_id":"138742","title":"Gemini AI Programming ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jXPCfB5TyN7pY4EyBYfJqGWZvpVIQ.png?v=1765067697\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n\u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003e Gemini AI Programming \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/146032150\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\u003cdiv\u003e \u003cb\u003eCreate your own custom AI applications on various platforms, including Colab, Android, and iOS, with Gemini, RamaIndex, and Langchain!\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e Gemini is a multimodal AI that processes various data such as text, images, videos, and voices, and can be used to create advanced AI services.\u003cbr\u003e \"Gemini AI Programming\" is an introductory book on developing \"chatbot AI\" using Google Gemini. It explains step-by-step how to utilize Gemini as well as how to create customized chatbot AI using the Gemini API.\u003cbr\u003e Additionally, it has been configured so that it can be implemented in Google Cloud services such as Google Colab, Android Studio, and Xcode.\u003cbr\u003e \u003cbr\u003eHere, we also introduce RamaIndex and LangChain, frameworks for developing LLM applications.\u003cbr\u003e RamaIndex is a framework that makes it very easy to build augmented search engines that answer questions using your own data, while LangChain is a framework suitable for building agents that manipulate tools such as APIs, functions, and databases with a natural language interface.\u003cbr\u003e I recommend this book to anyone who wants to start an AI project using Gemini, and I hope it will serve as an opportunity to utilize AI in various fields.\u003cbr\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cul\u003e\u003cli\u003e You can preview some of the book's contents.\u003cbr\u003e \u003cspan\u003ePreview\u003c\/span\u003e\n\n\u003c\/li\u003e\u003c\/ul\u003e\u003c\/div\u003e\n\u003c\/div\u003e \",\"\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003eChapter 1: Getting to Know Gemini\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.1 Getting to Know Gemini\u003cbr\u003e __1.1.1 Gemini\u003cbr\u003e __1.1.2 Gemini Model Types\u003cbr\u003e __1.1.3 Overview of Large-Scale Language Models\u003cbr\u003e __1.1.4 Getting to Know the Gemini API\u003cbr\u003e __1.1.5 Use Cases for Large-Scale Language Models  \u003cbr\u003e1.2 Gemini Start\u003cbr\u003e __1.2.1 Getting Started with Gemini\u003cbr\u003e __1.2.2 Gemini Advanced\u003cbr\u003e 1.3 Artificial Intelligence, Machine Learning, and Deep Learning\u003cbr\u003e __1.3.1 Artificial Intelligence, Machine Learning, and Deep Learning\u003cbr\u003e __1.3.2 Neurons and Neural Networks\u003cbr\u003e __1.3.3 Model building, training, and inference\u003cbr\u003e 1.4 Natural Language Processing and Deep Learning Models\u003cbr\u003e __1.4.1 History of Deep Learning Models in Natural Language Processing\u003cbr\u003e __1.4.2 Image Processing Using Deep Learning Models\u003cbr\u003e __1.4.3 Speech Processing Using Deep Learning\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 2 Using Gemini\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 2.1 How to Use Gemini\u003cbr\u003e __2.1.1 Gemini Screen Configuration\u003cbr\u003e __2.1.2 Key tasks that can be performed on Gemini\u003cbr\u003e 2.2 How to Use Google AI Studio\u003cbr\u003e __2.2.1 Getting Started with Google AI Studio\u003cbr\u003e __2.2.2 Screen composition of Google AI Studio\u003cbr\u003e __2.2.3 Get API Key\u003cbr\u003e __2.2.4 Writing new prompts and tuning models, libraries\u003cbr\u003e __2.2.5 Documentation\u003cbr\u003e __2.2.6 Settings\u003cbr\u003e __2.2.7 Toolbar\u003cbr\u003e __2.2.8 System Instructions\u003cbr\u003e __2.2.9 Running the prompt\u003cbr\u003e __2.2.10 Setting up execution  \u003cbr\u003e2.3 How to Use Vertex AI Studio\u003cbr\u003e __2.3.1 Getting Started with Vertex AI Studio\u003cbr\u003e __2.3.2 Vertex AI Gemini API Usage Fees\u003cbr\u003e __2.3.3 Screen composition of Vertex AI Studio\u003cbr\u003e __2.3.4 Left menu\u003cbr\u003e __2.3.5 Toolbar\u003cbr\u003e __2.3.6 System Instructions\u003cbr\u003e __2.3.7 Running the prompt\u003cbr\u003e __2.3.8 Setting up execution\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 3: Preparing the Python Development Environment\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 3.1 Python Overview\u003cbr\u003e __3.1.1 What is Python?\u003cbr\u003e 3.2 Getting to Know Google Colab\u003cbr\u003e __3.2.1 What is Google Colab?\u003cbr\u003e __3.2.2 Getting Started with Google Colab\u003cbr\u003e __3.2.3 Running a Python Script\u003cbr\u003e __3.2.4 Installing Python Packages\u003cbr\u003e __3.2.5 Adding Text\u003cbr\u003e __3.2.6 Configuring the Google Colab Screen\u003cbr\u003e __3.2.7 Google Colab's menu\u003cbr\u003e __3.2.8 Using GPU\u003cbr\u003e __3.2.9 Mount Google Drive\u003cbr\u003e __3.2.10 Google Colab Usage Limits and Countermeasures\u003cbr\u003e __3.2.11 Google Colab Pricing Plan\u003cbr\u003e 3.3 Basic Python Grammar\u003cbr\u003e __3.3.1 Outputting a string\u003cbr\u003e __3.3.2 Variables and Operators\u003cbr\u003e __3.3.3 string\u003cbr\u003e __3.3.4 List\u003cbr\u003e __3.3.5 Dictionary\u003cbr\u003e __3.3.6 Tuple\u003cbr\u003e __3.3.7 Control statements  \u003cbr\u003e__3.3.8 Functions and Lambda Expressions\u003cbr\u003e __3.3.9 class\u003cbr\u003e __3.3.10 Importing packages and calling components directly\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 4: Gemini API (Python Edition)\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 4.1 Text Generation\u003cbr\u003e __4.1.1 Overview of Text Generation\u003cbr\u003e __4.1.2 Gemini API Overview\u003cbr\u003e __4.1.3 Overview of Google AI Gemini API\u003cbr\u003e __4.1.4 Google AI Gemini API Fees\u003cbr\u003e __4.1.5 Get API Key\u003cbr\u003e __4.1.6 Preparing the Gemini API\u003cbr\u003e __4.1.7 Check the model list\u003cbr\u003e __4.1.8 Text Generation\u003cbr\u003e __4.1.9 Streaming\u003cbr\u003e __4.1.10 Chat\u003cbr\u003e __4.1.11 Creation Parameters\u003cbr\u003e __4.1.12 Check the number of tokens\u003cbr\u003e __4.1.13 Safety Settings\u003cbr\u003e __4.1.14 System Instructions\u003cbr\u003e __4.1.15 JSON mode\u003cbr\u003e 4.2 Multimodal\u003cbr\u003e __4.2.1 Multimodal Overview\u003cbr\u003e __4.2.2 Supported file formats\u003cbr\u003e __4.2.3 Preparing the Gemini API\u003cbr\u003e __4.2.4 Image Q\u0026amp;A\u003cbr\u003e __4.2.5 Image Query and Answer Using the File API\u003cbr\u003e __4.2.6 Voice Q\u0026amp;A\u003cbr\u003e __4.2.7 Video Q\u0026amp;A\u003cbr\u003e 4.3 Embedding\u003cbr\u003e __4.3.1 Embedding Overview\u003cbr\u003e __4.3.2 Preparing the Gemini API\u003cbr\u003e __4.3.3 Types of embedding models\u003cbr\u003e __4.3.4 How to use text-embedding-004  \u003cbr\u003e__4.3.5 Neighborhood Search Using Text-Embedding-004\u003cbr\u003e __4.3.6 How to use bge-m3\u003cbr\u003e __4.3.7 Neighborhood Search Using bge-m3\u003cbr\u003e 4.4 Function Calls\u003cbr\u003e __4.4.1 Overview of Function Calls\u003cbr\u003e __4.4.2 Preparing the Gemini API\u003cbr\u003e __4.4.3 Calling automatic functions\u003cbr\u003e __4.4.4 Setting up tools\u003cbr\u003e __4.4.5 Manually calling functions\u003cbr\u003e __4.4.6 Calling Parallel Functions\u003cbr\u003e 4.5 Fine Tuning\u003cbr\u003e __4.5.1 Overview of Fine Tuning\u003cbr\u003e __4.5.2 Gemini API Fees\u003cbr\u003e __4.5.3 Get the list of fine-tuned models\u003cbr\u003e __4.5.4 Preparing training data\u003cbr\u003e __4.5.5 Learning\u003cbr\u003e __4.5.6 Inference\u003cbr\u003e __4.5.7 Updating the Fine Tuning Model Description\u003cbr\u003e __4.5.8 Deleting a Fine Tuning Model\u003cbr\u003e __4.5.9 Credentials File\u003cbr\u003e 4.6 Vertex AI Gemini API\u003cbr\u003e __4.6.1 Overview of the Vertex AI Gemini API\u003cbr\u003e __4.6.2 Vertex AI Gemini API Fees\u003cbr\u003e __4.6.3 Preparing the service account key\u003cbr\u003e __4.6.4 Preparing the Vertex AI Gemini API\u003cbr\u003e __4.6.5 Generating Text\u003cbr\u003e __4.6.6 Image Q\u0026amp;A\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 5: Gemini API (Android Edition)\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e5.1 Text Generation\u003cbr\u003e __5.1.1 Overview of Text Generation\u003cbr\u003e __5.1.2 Overview of the Google AI Gemini API\u003cbr\u003e __5.1.3 Gemini API Fees\u003cbr\u003e __5.1.4 Retrieving API Keys\u003cbr\u003e __5.1.5 Preparing the Gemini API\u003cbr\u003e __5.1.6 Generating Text\u003cbr\u003e __5.1.7 Streaming\u003cbr\u003e __5.1.8 Chat\u003cbr\u003e __5.1.9 Creation Parameters\u003cbr\u003e __5.1.10 Safety Settings\u003cbr\u003e 5.2 Multimodal\u003cbr\u003e __5.2.1 Multimodal Overview\u003cbr\u003e __5.2.2 Preparing the Gemini API\u003cbr\u003e __5.2.3 Image Q\u0026amp;A\u003cbr\u003e 5.3 Local LLM\u003cbr\u003e __5.3.1 Overview of Local LLM\u003cbr\u003e __5.3.2 Gemini Nano and Gemma\u003cbr\u003e __5.3.3 Local language model execution environment on Android\u003cbr\u003e __5.3.4 Running the Llama.cpp Demo Application\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 6: Gemini API (iOS Edition)\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 6.1 Text Generation\u003cbr\u003e __6.1.1 Overview of Text Generation\u003cbr\u003e __6.1.2 Overview of Google AI Gemini API\u003cbr\u003e __6.1.3 Gemini API Fees\u003cbr\u003e __6.1.4 Retrieving API Keys\u003cbr\u003e __6.1.5 Preparing the Gemini API\u003cbr\u003e __6.1.6 Generating Text\u003cbr\u003e __6.1.7 Streaming\u003cbr\u003e __6.1.8 Chat\u003cbr\u003e __6.1.9 Creation Parameters\u003cbr\u003e __6.1.10 Safety Settings\u003cbr\u003e 6.2 Multimodal  \u003cbr\u003e__6.2.1 Multimodal Overview\u003cbr\u003e __6.2.2 Preparing the Gemini API\u003cbr\u003e __6.2.3 Image Q\u0026amp;A\u003cbr\u003e 6.3 Local LLM\u003cbr\u003e __6.3.1 Overview of Local LLM\u003cbr\u003e __6.3.2 Local LLM execution environment on iOS\u003cbr\u003e __6.3.3 Running the Llama.cpp Demo Application\u003cbr\u003e __6.3.4 Running the MLX Swift Demo Application\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 7 Rama Index\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 7.1 Starting the Rama Index\u003cbr\u003e __7.1.1 What is Rama Index?\u003cbr\u003e __7.1.2 Rama Index Core Steps\u003cbr\u003e __7.1.3 Preparing the Document\u003cbr\u003e __7.1.4 Preparing the Rama Index\u003cbr\u003e __7.1.5 Q\u0026amp;A using Rama Index\u003cbr\u003e __7.1.6 Saving and Loading Indexes\u003cbr\u003e 7.2 Customizing Rama Index\u003cbr\u003e __7.2.1 Overview of Rama Index Customization\u003cbr\u003e __7.2.2 Preparing the Rama Index\u003cbr\u003e __7.2.3 Preparing the Document\u003cbr\u003e __7.2.4 Customizing LLM\u003cbr\u003e __7.2.5 Customizing the Embedding Model\u003cbr\u003e __7.2.6 Customizing the Tokenizer\u003cbr\u003e __7.2.7 Customizing the Text Separator\u003cbr\u003e __7.2.8 Customizing the Query Engine\u003cbr\u003e __7.2.9 Reranker\u003cbr\u003e 7.3 Data Loader  \u003cbr\u003e__7.3.1 Data Loader Overview\u003cbr\u003e __7.3.2 Q\u0026amp;A using web pages\u003cbr\u003e __7.3.3 Q\u0026amp;A using YouTube videos\u003cbr\u003e 7.4 Vector Store\u003cbr\u003e __7.4.1 Overview of the Vector Store\u003cbr\u003e __7.4.2 Preparing the Rama Index\u003cbr\u003e __7.4.3 Preparing the Document\u003cbr\u003e __7.4.4 Order of use of Pie\u003cbr\u003e __7.4.5 Pinecon Overview and API Import\u003cbr\u003e __7.4.6 Pinecone usage order\u003cbr\u003e 7.5 rating\u003cbr\u003e __7.5.1 Evaluating the Rama Index\u003cbr\u003e __7.5.2 Preparing the Rama Index\u003cbr\u003e __7.5.3 Preparing the Document\u003cbr\u003e __7.5.4 Creating a Question Context Dataset\u003cbr\u003e __7.5.5 Retrieval Evaluation\u003cbr\u003e __7.5.6 Evaluating Response Performance\u003cbr\u003e\u003cbr\u003e \u003cb\u003eChapter 8: Langchain\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 8.1 Starting the Langchain\u003cbr\u003e __8.1.1 Langchain Overview\u003cbr\u003e __8.1.2 Langchain Usage Cases\u003cbr\u003e __8.1.3 Configuring the Langchain package\u003cbr\u003e __8.1.4 Introducing Langchain's modules\u003cbr\u003e __8.1.5 Preparing the Langchain\u003cbr\u003e __8.1.6 LLM\u003cbr\u003e __8.1.7 Prompt Template\u003cbr\u003e __8.1.8 Output Parser\u003cbr\u003e __8.1.9 Chain\u003cbr\u003e __8.1.10 Agent\u003cbr\u003e __8.1.11 Langsmith\u003cbr\u003e 8.2 LLM\u003cbr\u003e __8.2.1 LLM Overview\u003cbr\u003e __8.2.2 Preparing the Langchain\u003cbr\u003e __8.2.3 How to use LLM  \u003cbr\u003e__8.2.4 How to use ChatModel\u003cbr\u003e __8.2.5 Streaming\u003cbr\u003e __8.2.6 How to Use LLM in the Vertex AI Gemini API\u003cbr\u003e 8.3 Prompt Templates\u003cbr\u003e __8.3.1 Overview of the Prompt Template Module\u003cbr\u003e __8.3.2 Preparing the Langchain\u003cbr\u003e __8.3.3 How to use string prompt templates\u003cbr\u003e __8.3.4 How to use chat prompt templates\u003cbr\u003e __8.3.5 How to use message placeholders\u003cbr\u003e 8.4 Output Parser\u003cbr\u003e __8.4.1 Overview of the Output Parser\u003cbr\u003e __8.4.2 Preparing the Langchain\u003cbr\u003e __8.4.3 How to use the string output parser\u003cbr\u003e __8.4.4 How to use the simple JSON output parser\u003cbr\u003e __8.4.5 How to use the Pydantic Output Parser\u003cbr\u003e 8.5 chain\u003cbr\u003e __8.5.1 Chain Overview\u003cbr\u003e __8.5.2 LCEL Overview\u003cbr\u003e __8.5.3 Runnable Overview\u003cbr\u003e __8.5.4 Preparing the Langchain\u003cbr\u003e __8.5.5 How to use chains\u003cbr\u003e __8.5.6 How to use Runnable\u003cbr\u003e __8.5.7 Checking the input\/output schema of Runnable\u003cbr\u003e 8.6 Chatbot\u003cbr\u003e __8.6.1 Chatbot Overview\u003cbr\u003e __8.6.2 Preparing the Langchain\u003cbr\u003e __8.6.3 Preparing for LLM\u003cbr\u003e __8.6.4 Preparing the Chatbot\u003cbr\u003e __8.6.5 Custom Directives\u003cbr\u003e __8.6.6 Managing conversation history\u003cbr\u003e __8.6.7 Checking the rangesmith  \u003cbr\u003e8.7 Augmented Search Creation\u003cbr\u003e __8.7.1 Overview of Augmented Search Generation\u003cbr\u003e __8.7.2 Preparing the Langchain\u003cbr\u003e __8.7.3 Preparing the embedding model\u003cbr\u003e __8.7.4 Preparing the Vector Store\u003cbr\u003e __8.7.5 Preparing the Retriever\u003cbr\u003e __8.7.6 Implementing Augmented Search Generation\u003cbr\u003e __8.7.7 Processing Documents with Augmented Search Generation\u003cbr\u003e __8.7.8 Checking the rangesmith\u003cbr\u003e 8.8 Agent\u003cbr\u003e __8.8.1 Agent Overview\u003cbr\u003e __8.8.2 Preparing the Langchain\u003cbr\u003e __8.8.3 Preparing the embedding model\u003cbr\u003e __8.8.4 Preparing Tools\u003cbr\u003e __8.8.5 Implementing an Agent\u003cbr\u003e __8.8.6 Message Streaming\u003cbr\u003e __8.8.7 Implementing an Agent with Conversation History\u003cbr\u003e __8.8.8 Checking the rangesmith\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e \",\"\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eDetailed image\u003c\/b\u003e \u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cimg src=\"https:\/\/image.yes24.com\/momo\/TopCate5298\/MidCate7\/529764583.jpg\" border=\"0\" alt=\"Detailed Image 1\"\u003e\u003c\/div\u003e\u003c\/div\u003e \",\"\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eInto the book\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e This book provides a basic guide to developing with large-scale language models. \u003cbr\u003eIn particular, we will introduce the knowledge necessary to effectively design and implement applications by covering simple practical examples focusing on major libraries and platforms such as Gemini, RamaIndex, and LangChain.\u003cbr\u003e\u003cbr\u003e Libraries covered in this book, including Gemini, RamaIndex, and LangChain, go beyond simply leveraging AI model functions. They are useful for expanding the scope of AI applications in diverse areas, including data processing, information retrieval, and application design.\u003cbr\u003e I am confident that these technologies will play a key role in the AI ​​ecosystem, both now and in the future.\u003cbr\u003e\u003cbr\u003e AI is developing very rapidly.\u003cbr\u003e This will enable humans and machines to interact more naturally in the future.\u003cbr\u003e In particular, API-centric service design plays a critical role in maximizing the flexibility and scalability of AI. \u003cbr\u003eIn this trend, the combination of AI models and APIs has become an essential element in developing AI into a practical business tool.\u003cbr\u003e\u003cbr\u003e In fact, even while translating this book, Gemini continued its research, releasing new models such as 2.0 and Deep Research.\u003cbr\u003e That doesn't mean that the exercises and cases based on Gemini 1.5 are meaningless.\u003cbr\u003e Rather, I believe that if readers compare past models and the services based on them with the latest versions based on this book, they will be able to understand the flow of change and design and develop applications in a more advanced direction.\u003cbr\u003e\n\n\u003c\/div\u003e\n\u003cdiv\u003e --- From the \"Book Introduction\"\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e \",\"\u003cdiv\u003e\u003ch5\u003e \u003cb\u003ePublisher's Review\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003eThe first step to multimodal AI programming, starting with Gemini!\u003cbr\u003e Crossing text, images, videos, and voices\u003cbr\u003e The Complete Guide to AI Application Development!\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003eGemini, a generative AI developed by Google, is a multimodal AI that simultaneously processes various data such as text, images, videos, and voices.\u003cbr\u003e This can be used to create advanced AI services such as text + image analysis, voice-based chatbots, and video summary AI.\u003cbr\u003e\u003cbr\u003e This book aims to develop personalized chatbot AI applications using Gemini.\u003cbr\u003e It is structured around AI development using the Gemini API, and can be practiced in various development environments such as Colab, Android, and iOS.\u003cbr\u003e Additionally, we will explain RamaIndex and LangChain, which are standard frameworks for AI development, to guide you in developing advanced applications more easily.\u003cbr\u003e\u003cbr\u003e It goes beyond simply explaining examples, providing step-by-step exercises and code that can be followed and executed, allowing even novice developers to easily build AI applications. \u003cbr\u003eAdditionally, through this book, you can gain a comprehensive understanding of generative AI and learn how to apply it in practice.\u003cbr\u003e\n\n\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e \"]\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eDate of issue:\u003c\/strong\u003e May 13, 2025\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 388 pages | 720g | 183*235*16mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9791140713370 \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43893280276522,"sku":"138742","price":44.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/bc4d75e726198d301e495d355b66f35a.jpg?v=1765395458","url":"https:\/\/librairie.coreenne.fr\/en\/products\/138742","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}