Tensorflow Machine Learning Projects: Build 13 Real-world Projects With Advanced Numerical Computations Using The Python Ecosystem por Armando Fandango

Tensorflow Machine Learning Projects: Build 13 Real-world Projects With Advanced Numerical Computations Using The Python Ecosystem por Armando Fandango

Descargar Tensorflow Machine Learning Projects: Build 13 Real-world Projects With Advanced Numerical Computations Using The Python Ecosystem por Armando Fandango Epub y PDF

Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projectsKey FeaturesUse machine learning and deep learning principles to build real-world projectsGet to grips with TensorFlow's impressive range of module offeringsImplement projects on GANs, reinforcement learning, and capsule networkBook DescriptionTensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work.What you will learnUnderstand the TensorFlow ecosystem using various datasets and techniquesCreate recommendation systems for quality product recommendationsBuild projects using CNNs, NLP, and Bayesian neural networksPlay Pac-Man using deep reinforcement learningDeploy scalable TensorFlow-based machine learning systemsGenerate your own book script using RNNsWho this book is forTensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build end-to-end projects in the machine learning domain using supervised, unsupervised, and reinforcement learning techniques Table of ContentsOverview of Tensorflow and Machine LearningUsing Machine Learning to detect exoplanets in outer spaceSentiment Analysis in your browser using Tensorflow.jsDigit Classification using Tensorflow LiteSpeech to text and topic extraction using NLPPredicting Stock Prices using Gaussian Process RegressionCredit Card Fraud Detection using AutoencodersGenerating Uncertainty in Traffic Signs Classifier using Bayesian Neural NetworksGenerating Matching Shoe Bags from Shoe Images Using DiscoGANsClassifying Clothing Images using Capsule NetworksMaking Quality Product Recommendations Using TensorFlowObject detection at a large scale with TensorflowGenerating Book Scripts Using LSTMsPlaying Pacman using Deep Reinforcement Learning What is next?
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Autor (s): Armando Fandango
Título: Tensorflow Machine Learning Projects: Build 13 Real-world Projects With Advanced Numerical Computations Using The Python Ecosystem
Langue: Español
Formato: Epub

Armando Fandango con Tensorflow Machine Learning Projects: Build 13 Real-world Projects With Advanced Numerical Computations Using The Python Ecosystem

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