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Applied reinforcement learning with Python with OpenAI Gym, Tensorflow, and Keras Taweh Beysolow II by
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Publication details: Apress 2019
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Beginning Blockchain : A Beginner's Guide to Building Blockchain Solutions / by Bikramaditya Singhal, Gautam Dhameja, Priyansu Sekhar Panda. by
Edition: 1st ed. 2018.
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Publication details: Apress 2021
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Big data made easy Author: a working guide to the complete Hadoop toolset Michael Frampton by
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Publication details: Apress 2022
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Computer Vision Using Deep Learning : Author: , Neural Network Architectures with Python and Keras Vaibhav Verdhan by
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Data Science Solutions with Python Fast and Scalable Models Using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn Tshepo Chris Nokeri by
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Deep learning projects using TensorFlow 2 neural network development with Python and Keras Vinita Silaparasetty by
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Deep Learning with Python : A Hands-on Introduction / by Nikhil Ketkar. by
Edition: 1st ed. 2017.
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Publication details: Apress 2022
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Deep reinforcement learning with Python , with PyTorch, TensorFlow and OpenAI Gym Nimish Sanghi by
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Introducing Blockchain with Java Program, Implement, and Extend Blockchains with Java Spiro Buzharovski by
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Publication details: Apress 2022
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Machine learning with the Raspberry Pi experiments with data and computer vision Donald J Norris by
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Natural Language Processing Projects Build Next-Generation NLP Applications Using AI Techniques Akshay Kulkarni, Adarsha Shivananda, Anoosh Kulkarni by
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Practical explainable AI using Python artificial intelligence model explanations using Python-based libraries, extensions, and frameworks Pradeepta Mishra by
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Practical Hadoop ecosystem a definitive guide to Hadoop-related frameworks and tools Deepak Vohra by
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Reinforcement Learning : With Open AI, TensorFlow and Keras Using Python / by Abhishek Nandy, Manisha Biswas. by
Edition: 1st ed. 2018.
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Beginning app development with Flutter create cross-platform mobile apps Rap Payne by
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Building computer vision applications using artificial neural networks with step-by-step examples in OpenCV and TensorFlow with Python Shamshad Ansari by
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Generating a New Reality Lanham, Micheal From Autoencoders and Adversarial Networks to Deepfakes Micheal Lanham by
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Hyperparameter optimization in machine learning make your machine learning and deep learning models more efficient Tanay Agrawal by
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Learn to program with Kotlin from the basics to projects with text and image processing Tim Lavers by
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Practical Android : 14 Complete Projects on Advanced Techniques and Approaches / by Mark Wickham. by
Edition: 1st ed. 2018.
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Publication details: APress 2020
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Pro Android with Kotlin : Developing Modern Mobile Apps / by Peter Späth. by
Edition: 1st ed. 2018.
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Raspberry Pi GPU Audio Video Programming / by Jan Newmarch. by
Edition: 1st ed. 2017.
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Raspberry Pi Supercomputing and Scientific Programming : MPI4PY, NumPy, and SciPy for Enthusiasts / by Ashwin Pajankar. by
Edition: 1st ed. 2017.
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5G mobile core network Author design, deployment, automation, and testing strategies Rajaneesh Sudhakar Shetty by
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Angular 5 Projects : Learn to Build Single Page Web Applications Using 70+ Projects / by Mark Clow. by
Edition: 1st ed. 2018.
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Applied Deep Learning with TensorFlow 2 Learn to Implement Advanced Deep Learning Techniques with Python Umberto Michelucc by
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Artificial Neural Networks with Java Author: Tools for Building Neural Network Applications Igor Livshin by
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Artificial Neural Networks with Java Tools for Building Neural Network Applications Igor Livshin by
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Beginning 3D game assets development pipeline Villanueva, Nova., learn to integrate from Maya to Unity Nova Villanueva by
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Beginning Java 17 Fundamentals Sharan, Kishori (Software engineer); Davis, Adam L. Object-Oriented Programming in Java 17 Kishori Sharan, ; Adam L.Davis, by
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Beginning robotics with Raspberry Pi and Arduino using Python and OpenCV Jeff Cicolani by
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BigQuery for data warehousing Author: managed data analysis in the Google cloud Mark Mucchetti by
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Building machine learning and deep learning models on Google Cloud platform a comprehensive guide for beginners Ekaba Bisong by
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Business analytics using R - A practical approach Author: Rao, Umesh Hodeghatta; Nayak, Umesh; Nayak, Umesha Hodeghatta Umesh R; Nayak, Umesh; , Umesha Nayak by
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Cloud-Based Microservice Techniques, Challenges, and Solutions Chandra Rajasekharaiah by
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Computer Vision and Augmented Reality in iOS OpenCV and ARKit Applications Fathi, Ahmed Bekhit by
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Data Science with Raspberry Pi Real-Time Applications Using a Localized Cloud K. Mohaideen Abdul Kadhar ; Anand, G. by
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Deep Neuro-fuzzy systems with Python , Himanshu; Lone, Yunis Ahmad, with case studies and applications from industry Himanshu Singh;Yunis Ahmad Lone by
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Deep reinforcement learning in Unity ,, with Unity ML toolkit Abhilash Majumder by
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Hands-on Machine Learning with Python Implement Neural Network Solutions with Scikit-learn and PyTorch Ashwin Pajankar; Aditya Joshi by
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Introduction to deep learning using R a step-by-step guide to learning and implementing deep learning models using R Taweh Beysolow II by
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Lean entrepreneurship innovation in the modern enterprise George Watt; Howard Abrams by
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Mastering machine learning with Python in six steps a practical implementation guide to predictive data analytics using Python Manohar Swamynathan by
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Next-generation big data a practical guide to Apache Kudu, Impala, and Spark Butch Quinto by
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PHP solutions, Author: .; SpringerLink (Online service) dynamic web design made easy David Powers by
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Practical cyber forensics an incident-based approach to forensic investigations Niranjan Reddy by
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Practical smart device design and construction : Author: understanding smart technologies and how to build them yourself Christopher Harrold by
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