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Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
Python: Beginner's Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python

Develop real-world applications powered by the latest advances in intelligent systems

Key Features

  • Gain real-world contextualization using deep learning problems concerning research and application
  • Get to know the best practices to improve and optimize your machine...
Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala
Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.

Key Features

  • Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j
  • ...
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...
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...
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition

Build a strong foundation of machine learning algorithms in 7 days

Key Features

  • Use Python and its wide array of machine learning libraries to build predictive models
  • Learn the basics of the 7 most widely used machine learning algorithms within a week
  • Know...
Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles
Hands-On Neural Networks with Keras: Design and create neural networks using deep learning and artificial intelligence principles

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively

Key Features

  • Design and create neural network architectures on different domains using Keras
  • Integrate neural network models in your applications using this highly practical...
Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications
Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications

Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda

Key Features

  • Use Anaconda to find solutions for clustering, classification, and linear regression
  • Analyze your data efficiently with the most powerful data...
Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner
Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner
Using SAS Enterprise Miner, Barry de Ville's Decision Trees for Business Intelligence and Data Mining illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and...
Python Data Science Essentials: A practitioner's guide covering essential data science principles, tools, and techniques, 3rd Edition
Python Data Science Essentials: A practitioner's guide covering essential data science principles, tools, and techniques, 3rd Edition

Gain useful insights from your data using popular data science tools

Key Features

  • A one-stop guide to Python libraries such as pandas and NumPy
  • Comprehensive coverage of data science operations such as data cleaning and data manipulation
  • Choose scalable...
Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications
Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications
Discover hidden relationships among the variables in your data, and learn how to exploit these relationships.  This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications.  All algorithms include an intuitive explanation of operation, essential...
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner

Key Features

  • Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide
  • Train different types of neural networks using Tensorflow for...
Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions
Applied Deep Learning with Python: Use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions

A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examples

Key Features

  • Designed to iteratively develop the skills of Python users who don't have a data science background
  • Covers the key foundational concepts...
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