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Practical Data Science: A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets
Practical Data Science: A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets
Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.

The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data...
Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer.

Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware...
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Build and deploy powerful neural network models using the latest Java deep learning libraries

Key Features

  • Understand DL with Java by implementing real-world projects
  • Master implementations of various ANN models and build your own DL systems
  • Develop...
Practical Web Scraping for Data Science: Best Practices and Examples with Python
Practical Web Scraping for Data Science: Best Practices and Examples with Python

This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full...

TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition

Skip the theory and get the most out of Tensorflow to build production-ready machine learning models

Key Features

  • Exploit the features of Tensorflow to build and deploy machine learning models
  • Train neural networks to tackle real-world problems in Computer Vision and...
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras

Explore various Generative Adversarial Network architectures using the Python ecosystem

Key Features

  • Use different datasets to build advanced projects in the Generative Adversarial Network domain
  • Implement projects ranging from generating 3D shapes to a face aging...
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

Dive deeper into neural networks and get your models trained, optimized with this quick reference guide

Key Features

  • A quick reference to all important deep learning concepts and their implementations
  • Essential tips, tricks, and hacks to train a variety of deep learning...
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents

A practical guide to mastering reinforcement learning algorithms using Keras

Key Features

  • Build projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into action
  • Get to grips with Keras and practice on real-world unstructured...
Mastering Exploratory Analysis with pandas: Build an end-to-end data analysis workflow with Python
Mastering Exploratory Analysis with pandas: Build an end-to-end data analysis workflow with Python

Explore Python frameworks like pandas, Jupyter notebooks, and Matplotlib to build data pipelines and data visualization

Key Features

  • Learn to set up data analysis pipelines with pandas and Jupyter notebooks
  • Effective techniques for data selection, manipulation, and...
Hands-On Deep Learning for Images with TensorFlow: Build intelligent computer vision applications using TensorFlow and Keras
Hands-On Deep Learning for Images with TensorFlow: Build intelligent computer vision applications using TensorFlow and Keras

Explore TensorFlow's capabilities to perform efficient deep learning on images

Key Features

  • Discover image processing for machine vision
  • Build an effective image classification system using the power of CNNs
  • Leverage TensorFlow's capabilities to...
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python

Automate data and model pipelines for faster machine learning applications

Key Features

  • Build automated modules for different machine learning components
  • Understand each component of a machine learning pipeline in depth
  • Learn to use different open source...
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