{"product_id":"139256","title":"Machine Learning \u0026amp; Deep Learning for Developers ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jXPBvmCVFV6hGJ77ui6xlwJsBugBv.png?v=1765074195\" 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 Machine Learning \u0026amp; Deep Learning for Developers \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\/112028850\/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\u003eDedicated to developers who find math difficult\u003cbr\u003e Hands-on Machine Learning Guidebook\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e As the adoption of artificial intelligence technology increases, the skills required of developers are also increasing.\u003cbr\u003e Artificial intelligence is transforming industries. How can we master it wisely and effectively? This book aims to guide developers through solving various problems they face using machine learning and help them level up as machine learning and AI developers.\u003cbr\u003e \u003cbr\u003eThe content is based on online courses chosen by tens of thousands of people, and does not cover complex or difficult formulas. Instead, you learn key concepts by practicing various example codes.\u003cbr\u003e We'll implement a variety of scenarios you'll encounter in the world of machine learning, and also introduce sequence modeling for computer vision, natural language processing, web, mobile, cloud, and embedded runtimes.\u003cbr\u003e After reading this book, you will soon be upgraded to an AI developer who can freely navigate the world of machine learning and artificial intelligence with Python and TensorFlow.\u003cbr\u003e\n\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\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003e[PART I: Building the Model]\u003cbr\u003e\u003cbr\u003e Chapter 1: Introduction to TensorFlow\u003c\/b\u003e\u003cbr\u003e 1.1 What is machine learning?\u003cbr\u003e 1.2 Limitations of Traditional Programming\u003cbr\u003e 1.3 From Programming to Learning\u003cbr\u003e 1.4 TensorFlow\u003cbr\u003e 1.5 Using TensorFlow\u003cbr\u003e 1.6 Getting Started with Machine Learning\u003cbr\u003e 1.7 In conclusion\u003cbr\u003e \u003cbr\u003e\u003cb\u003eCHAPTER 2: INTRODUCTION TO COMPUTER VISION\u003c\/b\u003e\u003cbr\u003e 2.1 Recognizing Clothing Items\u003cbr\u003e 2.2 Neurons for Computer Vision\u003cbr\u003e 2.3 Neural network design\u003cbr\u003e 2.4 Training the Neural Network\u003cbr\u003e 2.5 Examining the Model Output\u003cbr\u003e 2.6 Training longer: Overfitting\u003cbr\u003e 2.7 Early termination of training\u003cbr\u003e 2.8 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 3 ADVANCED COMPUTER VISION: Detecting Features in Images\u003c\/b\u003e\u003cbr\u003e 3.1 Convolution\u003cbr\u003e 3.2 Pooling\u003cbr\u003e 3.3 Creating a Convolutional Neural Network\u003cbr\u003e 3.4 Examining Convolutional Neural Networks\u003cbr\u003e 3.5 Building a CNN that Distinguishes Speech from People\u003cbr\u003e 3.6 Image multiplication\u003cbr\u003e 3.7 Transfer Learning\u003cbr\u003e 3.8 Multi-classification\u003cbr\u003e 3.9 Dropout Regulation\u003cbr\u003e 3.10 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 4: Using Public Datasets with TensorFlow Datasets\u003c\/b\u003e\u003cbr\u003e 4.1 Getting Started with TensorFlow Datasets\u003cbr\u003e 4.2 Using TensorFlow Datasets in Keras Models\u003cbr\u003e 4.3 Using mapping functions for data augmentation\u003cbr\u003e 4.4 Using Custom Splits\u003cbr\u003e 4.5 Understanding TFRecord\u003cbr\u003e 4.6 ETL Process for Data Management in TensorFlow\u003cbr\u003e 4.7 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 5: INTRODUCTION TO NATURAL LANGUAGE PROCESSING\u003c\/b\u003e \u003cbr\u003e5.1 Encoding Language into Numbers\u003cbr\u003e 5.2 Stopword Removal and Text Cleansing\u003cbr\u003e 5.3 Handling Real Data\u003cbr\u003e 5.4 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 6: Emotional Programming Using Embeddings\u003c\/b\u003e\u003cbr\u003e 6.1 Constructing the meaning of words\u003cbr\u003e 6.2 Embedding in TensorFlow\u003cbr\u003e 6.3 Embedding Visualization\u003cbr\u003e 6.4 Using Pretrained Embeddings from TensorFlow Hub\u003cbr\u003e 6.5 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 7 Recurrent Neural Networks for Natural Language Processing\u003c\/b\u003e\u003cbr\u003e 7.1 Circular Structure\u003cbr\u003e 7.2 Extending the cycle to language\u003cbr\u003e 7.3 Building a Text Classifier with RNNs\u003cbr\u003e 7.4 Using Pretrained Embeddings in RNNs\u003cbr\u003e 7.5 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 8: Generating Text with TensorFlow\u003c\/b\u003e\u003cbr\u003e 8.1 Converting a sequence to an input sequence\u003cbr\u003e 8.2 Creating a Model\u003cbr\u003e 8.3 Creating Text\u003cbr\u003e 8.4 Expanding the Dataset\u003cbr\u003e 8.5 Changing the model structure\u003cbr\u003e 8.6 Improving Data\u003cbr\u003e 8.7 Character-based encoding\u003cbr\u003e 8.8 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 9 Understanding Sequence and Time Series Data\u003c\/b\u003e\u003cbr\u003e 9.1 Common Features of Time Series\u003cbr\u003e 9.2 Time series forecasting techniques\u003cbr\u003e 9.3 In conclusion\u003cbr\u003e \u003cbr\u003e\u003cb\u003eCHAPTER 10: Building a Machine Learning Model to Predict Sequences\u003c\/b\u003e\u003cbr\u003e 10.1 Creating a Windows Dataset\u003cbr\u003e 10.2 Creating a DNN and Training It with Sequence Data\u003cbr\u003e 10.3 Evaluating DNN Results\u003cbr\u003e 10.4 Looking at the overall forecast\u003cbr\u003e 10.5 Tuning the Learning Rate\u003cbr\u003e 10.6 Tuning Hyperparameters with Keras Tuner\u003cbr\u003e 10.7 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 11 Convolutional Neural Networks and Recurrent Neural Networks for Sequence Models\u003c\/b\u003e\u003cbr\u003e 11.1 Convolution for Sequence Data\u003cbr\u003e 11.2 Using NASA Weather Data\u003cbr\u003e 11.3 Modeling Sequences with RNNs\u003cbr\u003e 11.4 Other circulation layers\u003cbr\u003e 11.5 Using Dropout\u003cbr\u003e 11.6 Using Bidirectional RNNs\u003cbr\u003e 11.7 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003e[PART II Using the Model]\u003cbr\u003e\u003cbr\u003e Chapter 12: Introducing TensorFlow Lite\u003c\/b\u003e\u003cbr\u003e 12.1 What is TensorFlow Lite?\u003cbr\u003e 12.2 Converting a Trained Model to TensorFlow Lite\u003cbr\u003e 12.3 Converting an Image Classifier Built with Transfer Learning to TensorFlow Lite\u003cbr\u003e 12.4 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 13 Using TensorFlow Lite in Android Apps\u003c\/b\u003e\u003cbr\u003e 13.1 What is Android Studio? \u003cbr\u003e13.2 Creating Your First TensorFlow Lite Android App\u003cbr\u003e 13.3 Creating an App that Processes Images\u003cbr\u003e 13.4 TensorFlow Lite Sample App (for Android)\u003cbr\u003e 13.5 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 14 Using TensorFlow Lite in iOS Apps\u003c\/b\u003e\u003cbr\u003e 14.1 Creating Your First TensorFlow Lite App with Xcode\u003cbr\u003e 14.2 One Step Further: Image Processing\u003cbr\u003e 14.3 TensorFlow Lite Sample App (for iOS)\u003cbr\u003e 14.4 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 15: Introduction to TensorFlow.js\u003c\/b\u003e\u003cbr\u003e 15.1 What is TensorFlow.js?\u003cbr\u003e 15.2 Installing and Running Brackets\u003cbr\u003e 15.3 Creating Your First TensorFlow.js Model\u003cbr\u003e 15.4 Building an Iris Classifier\u003cbr\u003e 15.5 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 16: Training Computer Vision Models in TensorFlow.js\u003c\/b\u003e\u003cbr\u003e 16.1 JavaScript Considerations for TensorFlow Developers\u003cbr\u003e 16.2 Building a CNN with JavaScript\u003cbr\u003e 16.3 Using Callbacks for Visualization\u003cbr\u003e 16.4 Training with the MNIST Dataset\u003cbr\u003e 16.5 Performing Inference on Images with TensorFlow.js\u003cbr\u003e 16.6 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 17 Converting and Reusing Python Models\u003c\/b\u003e \u003cbr\u003e17.1 Converting Python-based models to JavaScript\u003cbr\u003e 17.2 Using a pre-transformed model\u003cbr\u003e 17.3 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 18 Transfer Learning in JavaScript\u003c\/b\u003e\u003cbr\u003e 18.1 Performing Transfer Learning with MobileNet\u003cbr\u003e 18.2 Transfer Learning with TensorFlow Hub\u003cbr\u003e 18.3 Transfer Learning with TensorFlow.org\u003cbr\u003e 18.4 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 19 Deploying with TensorFlow Serving\u003c\/b\u003e\u003cbr\u003e 19.1 What is TensorFlow Serving?\u003cbr\u003e 19.2 Installing TensorFlow Serving\u003cbr\u003e 19.3 Building and Deploying Models\u003cbr\u003e 19.4 In conclusion\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 20 AI Ethics, Fairness, and Privacy\u003c\/b\u003e\u003cbr\u003e 20.1 Fairness in Programming\u003cbr\u003e 20.2 Fairness in Machine Learning\u003cbr\u003e 20.3 Tools for Fairness\u003cbr\u003e 20.4 Federated Learning\u003cbr\u003e 20.5 Google's AI Principles\u003cbr\u003e 20.6 In conclusion\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\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\/TopCate3922\/MidCate010\/392195257.jpg\" border=\"0\" alt=\"Detailed Image 1\"\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\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\u003eRecommended by Andrew Ng, one of the four leading experts in artificial intelligence\u003cbr\u003e A Machine Learning Guidebook by, for, and of Developers\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003eWe've truly entered the era of artificial intelligence! AI technology has been growing rapidly, and various industries, including finance, education, distribution, and manufacturing, are rushing to adopt it.\u003cbr\u003e In keeping with the times, AI-related education is diversifying and the age of participants is getting younger. However, many developers still find it difficult to take their first steps in machine learning and deep learning.\u003cbr\u003e If you're a developer who wants to learn artificial intelligence properly but finds complex formulas burdensome, or if you want to start machine learning with Python code without difficult theories, this book is the perfect time to take your first step into the world of machine learning!\u003cbr\u003e\u003cbr\u003e This book explains machine learning and TensorFlow from a developer's perspective and guides you through installing TensorFlow for practical use. \u003cbr\u003eWe'll implement simple models ourselves and build machine learning and deep learning models using various datasets, including Fashion MNIST, Horse-Person, Rock, Paper, Scissors, Sarcasm, and Dog-Cat datasets.\u003cbr\u003e This book is a comprehensive machine learning gift set for developers, covering computer vision, convolutional neural networks, recurrent neural networks, as well as TensorFlow Lite, TensorFlow.js, and TensorFlow Serving.\u003cbr\u003e Learn machine learning step by step with clear, practical explanations of concepts and example code.\u003cbr\u003e We support you as you level up as AI developers.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e \u003cb\u003eTarget audience\u003c\/b\u003e\u003cbr\u003e ● Developers who want to get started with machine learning but don't know where to start\u003cbr\u003e Anyone who wants to learn machine learning concepts by directly executing Python code without difficult math or theory\u003cbr\u003e\u003cbr\u003e \u003cb\u003eKey Contents\u003c\/b\u003e\u003cbr\u003e ● Creating various model structures with TensorFlow\u003cbr\u003e ● Building a model with a neural network with one neuron \u003cbr\u003e● Detecting image features using computer vision\u003cbr\u003e ● Tokenize and order words and sentences using natural language processing\u003cbr\u003e ● Using models on mobile devices with TensorFlow Lite\u003cbr\u003e Deploying models to the web or cloud with TensorFlow Serving \u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\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\u003ePublication date:\u003c\/strong\u003e August 24, 2022\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 464 pages | 922g | 183*235*30mm\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 9791169210126\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN10:\u003c\/strong\u003e 1169210120 \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":43893347319850,"sku":"139256","price":45.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/d11968de4eeec5a97ab6292bbed3cb0b.jpg?v=1765397701","url":"https:\/\/librairie.coreenne.fr\/en\/products\/139256","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}