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Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Artificial Intelligence for Robotics: Build intelligent robots that perform human tasks using AI techniques
Artificial Intelligence for Robotics: Build intelligent robots that perform human tasks using AI techniques

Bring a new degree of interconnectivity to your world by building your own intelligent robots

Key Features

  • Leverage fundamentals of AI and robotics
  • Work through use cases to implement various machine learning algorithms
  • Explore Natural Language Processing...
Learning Python Networking: A complete guide to build and deploy strong networking capabilities using Python 3.7 and Ansible , 2nd Edition
Learning Python Networking: A complete guide to build and deploy strong networking capabilities using Python 3.7 and Ansible , 2nd Edition

Achieve improved network programmability and automation by leveraging powerful network programming concepts, algorithms, and tools

Key Features

  • Deal with remote network servers using SSH, FTP, SNMP and LDAP protocols.
  • Design multi threaded and event-driven architectures...
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances

Create AI applications in Python and lay the foundations for your career in data science

Key Features

  • Practical examples that explain key machine learning algorithms
  • Explore neural networks in detail with interesting examples
  • Master core AI concepts with...
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

Key Features

  • Implement machine learning algorithms to build, train, and validate algorithmic models
  • Create your own algorithmic design process to apply...
Introduction to Deep Learning Business Applications for Developers: From Conversational Bots in Customer Service to Medical Image Processing
Introduction to Deep Learning Business Applications for Developers: From Conversational Bots in Customer Service to Medical Image Processing
Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and...
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques
Artificial Intelligence for Big Data: Complete guide to automating Big Data solutions using Artificial Intelligence techniques

Build next-generation artificial intelligence systems with Java

Key Features

  • Implement AI techniques to build smart applications using Deeplearning4j
  • Perform big data analytics to derive quality insights using Spark MLlib
  • Create self-learning systems using...
Data Science Fundamentals for Python and MongoDB
Data Science Fundamentals for Python and MongoDB
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate....
Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems
Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner....

Learning JavaScript Data Structures and Algorithms: Write complex and powerful JavaScript code using the latest ECMAScript, 3rd Edition
Learning JavaScript Data Structures and Algorithms: Write complex and powerful JavaScript code using the latest ECMAScript, 3rd Edition

Create classic data structures and algorithms such as depth-first search and breadth-first search, learn recursion, as well as create and use a heap data structure using JavaScript

Key Features

  • Implement common data structures and the associated algorithms along with the context in which...
Practical Convolutional Neural Networks: Implement advanced deep learning models using Python
Practical Convolutional Neural Networks: Implement advanced deep learning models using Python

One stop guide to implementing award-winning, and cutting-edge CNN architectures

Key Features

  • Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques
  • Implement CNN models on image classification, transfer learning, Object Detection,...
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...
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