Ґері В. Левандовскi - ebooki
Tytuły autora: Ґері В. Левандовскi dostępne w księgarni Ebookpoint
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Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
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Uczenie maszynowe z użyciem Scikit-Learn i TensorFlow. Wydanie II
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Hands-On Explainable AI (XAI) with Python. Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps
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The Deep Learning Workshop. Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras
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The Applied TensorFlow and Keras Workshop. Develop your practical skills by working through a real-world project and build your own Bitcoin price prediction tracker
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The Data Analysis Workshop. Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way
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The Data Wrangling Workshop. Create your own actionable insights using data from multiple raw sources - Second Edition
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The Deep Learning with Keras Workshop. Learn how to define and train neural network models with just a few lines of code
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The Unsupervised Learning Workshop. Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions
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The Data Visualization Workshop. A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
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The Applied AI and Natural Language Processing Workshop. Explore practical ways to transform your simple projects into powerful intelligent applications
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The Computer Vision Workshop. Develop the skills you need to use computer vision algorithms in your own artificial intelligence projects
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The Applied Artificial Intelligence Workshop. Start working with AI today, to build games, design decision trees, and train your own machine learning models
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Hands-On Simulation Modeling with Python. Develop simulation models to get accurate results and enhance decision-making processes
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Deep Learning for Coders with fastai and PyTorch
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Raspberry Pi Computer Vision Programming. Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3 - Second Edition
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Hands-On Python Natural Language Processing. Explore tools and techniques to analyze and process text with a view to building real-world NLP applications
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Practical Data Analysis Using Jupyter Notebook. Learn how to speak the language of data by extracting useful and actionable insights using Python
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Uczenie maszynowe w Pythonie. Leksykon kieszonkowy
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40 Algorithms Every Programmer Should Know. Hone your problem-solving skills by learning different algorithms and their implementation in Python
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Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks
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Programowanie w TypeScript
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Python. Instrukcje dla programisty. Wydanie II
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Python Automation Cookbook. 75 Python automation recipes for web scraping; data wrangling; and Excel, report, and email processing - Second Edition
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Uczenie głębokie od zera. Podstawy implementacji w Pythonie
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Hands-On Web Penetration Testing with Metasploit. The subtle art of using Metasploit 5.0 for web application exploitation
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Czysty kod w Pythonie
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Hands-On Python Deep Learning for the Web. Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow
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Mastering Computer Vision with TensorFlow 2.x. Build advanced computer vision applications using machine learning and deep learning techniques
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High Performance Python. 2nd Edition
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MicroPython Projects. A do-it-yourself guide for embedded developers to build a range of applications using Python
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Network Automation Cookbook. Proven and actionable recipes to automate and manage network devices using Ansible
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Python Image Processing Cookbook. Over 60 recipes to help you perform complex image processing and computer vision tasks with ease
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Interactive Data Visualization with Python. Present your data as an effective and compelling story - Second Edition
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Hands-On One-shot Learning with Python. Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch
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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter. Build scalable real-world projects to implement end-to-end neural networks on Android and iOS
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Django 3 By Example. Build powerful and reliable Python web applications from scratch - Third Edition
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Quantum Computing and Blockchain in Business. Exploring the applications, challenges, and collision of quantum computing and blockchain
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Hands-On Exploratory Data Analysis with Python. Perform EDA techniques to understand, summarize, and investigate your data
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Django 3 Web Development Cookbook. Actionable solutions to common problems in Python web development - Fourth Edition
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OpenCV 4 with Python Blueprints. Build creative computer vision projects with the latest version of OpenCV 4 and Python 3 - Second Edition
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Flask. Tworzenie aplikacji internetowych w Pythonie. Wydanie II
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Architecture Patterns with Python. Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices
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Advanced Deep Learning with TensorFlow 2 and Keras. Apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more - Second Edition
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Artificial Intelligence By Example. Acquire advanced AI, machine learning, and deep learning design skills - Second Edition
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The Supervised Learning Workshop. Predict outcomes from data by building your own powerful predictive models with machine learning in Python - Second Edition
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Learning OpenCV 4 Computer Vision with Python 3. Get to grips with tools, techniques, and algorithms for computer vision and machine learning - Third Edition
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Artificial Intelligence with Python. Your complete guide to building intelligent apps using Python 3.x - Second Edition
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Deep Reinforcement Learning Hands-On. Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more - Second Edition
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Hands-On Genetic Algorithms with Python. Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems
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Hands-On Music Generation with Magenta. Explore the role of deep learning in music generation and assisted music composition
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Mastering Machine Learning Algorithms. Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work - Second Edition
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Python for Finance Cookbook. Over 50 recipes for applying modern Python libraries to financial data analysis
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Mastering Python Networking. Your one-stop solution to using Python for network automation, programmability, and DevOps - Third Edition
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Using Asyncio in Python. Understanding Python's Asynchronous Programming Features
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Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
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Cyber Minds. Insights on cybersecurity across the cloud, data, artificial intelligence, blockchain, and IoT to keep you cyber safe
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Hands-On Reinforcement Learning for Games. Implementing self-learning agents in games using artificial intelligence techniques
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Cybersecurity - Attack and Defense Strategies. Counter modern threats and employ state-of-the-art tools and techniques to protect your organization against cybercriminals - Second Edition
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Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition
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Hands-On Neuroevolution with Python. Build high-performing artificial neural network architectures using neuroevolution-based algorithms
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Advanced Deep Learning with Python. Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch
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Python for DevOps. Learn Ruthlessly Effective Automation
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Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 - Third Edition
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Hands-On Machine Learning with TensorFlow.js. A guide to building ML applications integrated with web technology using the TensorFlow.js library
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Hands-On Docker for Microservices with Python. Design, deploy, and operate a complex system with multiple microservices using Docker and Kubernetes
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Introducing Python. Modern Computing in Simple Packages. 2nd Edition
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The Python Workshop. Learn to code in Python and kickstart your career in software development or data science
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PyTorch 1.x Reinforcement Learning Cookbook. Over 60 recipes to design, develop, and deploy self-learning AI models using Python
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Mastering pandas. A complete guide to pandas, from installation to advanced data analysis techniques - Second Edition
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Data Mining. Eksploracja danych w sieciach społecznościowych. Wydanie III
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Practical Deep Learning for Cloud, Mobile, and Edge. Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow
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Python GUI Programming Cookbook. Develop functional and responsive user interfaces with tkinter and PyQt5 - Third Edition
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Algorytmy Data Science. Siedmiodniowy przewodnik. Wydanie II
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Przetwarzanie i analiza danych w języku Python
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Deep Learning from Scratch. Building with Python from First Principles
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Learn Python by Building Data Science Applications. A fun, project-based guide to learning Python 3 while building real-world apps
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Machine Learning Pocket Reference. Working with Structured Data in Python
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Hands-On Artificial Intelligence for Cybersecurity. Implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies
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Hands-On Data Analysis with Pandas. Efficiently perform data collection, wrangling, analysis, and visualization using Python
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Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow
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Ekstrakcja danych z językiem Python. Pozyskiwanie danych z internetu. Wydanie II
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Hands-On Ensemble Learning with Python. Build highly optimized ensemble machine learning models using scikit-learn and Keras
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Hands-On Web Scraping with Python. Perform advanced scraping operations using various Python libraries and tools such as Selenium, Regex, and others
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Python na poważnie
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Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
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Python GUI Programming - A Complete Reference Guide. Develop responsive and powerful GUI applications with PyQt and Tkinter
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Django 2. Praktyczne tworzenie aplikacji sieciowych. Wydanie II
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Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks
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Geospatial Data Science Quick Start Guide. Effective techniques for performing smarter geospatial analysis using location intelligence
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Hands-On Computer Vision with TensorFlow 2. Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras
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Hands-On Neural Networks. Learn how to build and train your first neural network model using Python
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IronPython Studio
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Applied Unsupervised Learning with Python. Discover hidden patterns and relationships in unstructured data with Python
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Supervised Machine Learning with Python. Develop rich Python coding practices while exploring supervised machine learning
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Training Systems using Python Statistical Modeling. Explore popular techniques for modeling your data in Python
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Hands-On GPU Computing with Python. Explore the capabilities of GPUs for solving high performance computational problems
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Expert Python Programming. Become a master in Python by learning coding best practices and advanced programming concepts in Python 3.7 - Third Edition
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Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras
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Mastering Python for Finance. Implement advanced state-of-the-art financial statistical applications using Python - Second Edition
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Applied Supervised Learning with Python. Use scikit-learn to build predictive models from real-world datasets and prepare yourself for the future of machine learning
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Odoo 12 Development Cookbook. 190+ unique recipes to build effective enterprise and business applications - Third Edition
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Hands-On Q-Learning with Python. Practical Q-learning with OpenAI Gym, Keras, and TensorFlow
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Python Reinforcement Learning. Solve complex real-world problems by mastering reinforcement learning algorithms using OpenAI Gym and TensorFlow
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Python. Kurs dla nauczycieli i studentów
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Big Data Analysis with Python. Combine Spark and Python to unlock the powers of parallel computing and machine learning
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Python. Szybko i prosto. Wydanie III
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Data Science for Marketing Analytics. Achieve your marketing goals with the data analytics power of Python
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Hands-On Deep Learning for Games. Leverage the power of neural networks and reinforcement learning to build intelligent games
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Mobile Artificial Intelligence Projects. Develop seven projects on your smartphone using artificial intelligence and deep learning techniques
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Natural Language Processing Fundamentals. Build intelligent applications that can interpret the human language to deliver impactful results
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Python Machine Learning Cookbook. Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets - Second Edition
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Building Serverless Microservices in Python. A complete guide to building, testing, and deploying microservices using serverless computing on AWS
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Hands-On Big Data Analytics with PySpark. Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs
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Learning Python Networking. A complete guide to build and deploy strong networking capabilities using Python 3.7 and Ansible - Second Edition
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Mastering OpenCV 4 with Python. A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7
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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide. A practical guide to building neural networks using Microsoft's open source deep learning framework
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Mastering Geospatial Development with QGIS 3.x. An in-depth guide to becoming proficient in spatial data analysis using QGIS 3.4 and 3.6 with Python - Third Edition
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Mastering Ansible. Effectively automate configuration management and deployment challenges with Ansible 2.7 - Third Edition
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Klasyczne problemy informatyki w Pythonie