Ryan Marvin, Mark Nganga, Amos Omondi - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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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 Data Visualization Workshop. A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
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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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Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
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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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Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks
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Uczenie głębokie od zera. Podstawy implementacji w Pythonie
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Analytical Skills for AI and Data Science. Building Skills for an AI-Driven Enterprise
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Practical Synthetic Data Generation. Balancing Privacy and the Broad Availability of Data
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Hands-On Machine Learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines
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Hands-On Deep Learning with R. A practical guide to designing, building, and improving neural network models using R
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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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Przetwarzanie i analiza obrazów w systemach przemysłowych. Wybrane zastosowania
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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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Hands-On Machine Learning with ML.NET. Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
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Człowiek na rozdrożu. Sztuczna inteligencja 25 punktów widzenia
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The Practitioner's Guide to Graph Data. Applying Graph Thinking and Graph Technologies to Solve Complex Problems
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Język R. Receptury. Analiza danych, statystyka i przetwarzanie grafiki. Wydanie II
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The Applied SQL Data Analytics Workshop. Develop your practical skills and prepare to become a professional data analyst - Second Edition
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Deep Learning with R Cookbook. Over 45 unique recipes to delve into neural network techniques using R 3.5.x
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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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The Data Science Workshop. A New, Interactive Approach to Learning Data Science
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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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Tableau Desktop Certified Associate: Exam Guide. Develop your Tableau skills and prepare for Tableau certification with tips from industry experts
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Advanced Deep Learning with R. Become an expert at designing, building, and improving advanced neural network models using R
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TinyML. Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
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TensorFlow. 13 praktycznych projektów wykorzystujących uczenie maszynowe
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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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Big data, nauka o danych i AI bez tajemnic. Podejmuj lepsze decyzje i rozwijaj swój biznes!
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Microsoft Excel 2019 Przetwarzanie danych za pomocą tabel przestawnych
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Głębokie uczenie z TensorFlow. Od regresji liniowej po uczenie przez wzmacnianie
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Managing Data Science. Effective strategies to manage data science projects and build a sustainable team
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Learn Algorithmic Trading. Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis
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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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Elasticsearch 7 Quick Start Guide. Get up and running with the distributed search and analytics capabilities of Elasticsearch
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Google BigQuery: The Definitive Guide. Data Warehousing, Analytics, and Machine Learning at Scale
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R Bioinformatics Cookbook. Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
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Algorytmy Data Science. Siedmiodniowy przewodnik. Wydanie II
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arc42 by Example. Software architecture documentation in practice
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Practical Automated Machine Learning on Azure. Using Azure Machine Learning to Quickly Build AI Solutions
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Practical Data Science with SAP. Machine Learning Techniques for Enterprise Data
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Learn Power BI. A beginner's guide to developing interactive business intelligence solutions using Microsoft Power BI
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Deep Learning
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Machine Learning for OpenCV 4. Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn - Second Edition
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Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications
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SQL for Data Analytics. Perform fast and efficient data analysis with the power of SQL
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Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go
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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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Hands-On Ensemble Learning with Python. Build highly optimized ensemble machine learning models using scikit-learn and Keras
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Deep Learning. Receptury
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Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
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R Cookbook. Proven Recipes for Data Analysis, Statistics, and Graphics. 2nd Edition
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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 Exploratory Data Analysis with R. Become an expert in exploratory data analysis using R packages
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Advanced Machine Learning with R. Tackle data analytics and machine learning challenges and build complex applications with R 3.5
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Deep Learning with R for Beginners. Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet
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Mastering Machine Learning on AWS. Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
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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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Hands-On Machine Learning with Microsoft Excel 2019. Build complete data analysis flows, from data collection to visualization
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Machine Learning for Data Mining. Improve your data mining capabilities with advanced predictive modeling
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Machine Learning with Scala Quick Start Guide. Leverage popular machine learning algorithms and techniques and implement them in Scala
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PyTorch Deep Learning Hands-On. Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily
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Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
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Data Science for Marketing Analytics. Achieve your marketing goals with the data analytics power of Python
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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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Hands-On Big Data Analytics with PySpark. Analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs
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Hands-On Machine Learning with IBM Watson. Leverage IBM Watson to implement machine learning techniques and algorithms using Python
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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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TensorFlow 2.0 Quick Start Guide. Get up to speed with the newly introduced features of TensorFlow 2.0
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Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
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Python. Uczenie maszynowe. Wydanie II
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Building Computer Vision Projects with OpenCV 4 and C++. Implement complex computer vision algorithms and explore deep learning and face detection
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Data Wrangling with Python. Creating actionable data from raw sources
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Hands-On Business Intelligence with Qlik Sense. Implement self-service data analytics with insights and guidance from Qlik Sense experts
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Learn Chart.js. Create interactive visualizations for the Web with Chart.js 2
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Mastering Tableau 2019.1. An expert guide to implementing advanced business intelligence and analytics with Tableau 2019.1 - Second Edition
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Neural Networks with Keras Cookbook. Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots
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Python Machine Learning By Example. Implement machine learning algorithms and techniques to build intelligent systems - Second Edition
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Apache Spark Quick Start Guide. Quickly learn the art of writing efficient big data applications with Apache Spark
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Ensemble Machine Learning Cookbook. Over 35 practical recipes to explore ensemble machine learning techniques using Python
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Hands-On Data Science with the Command Line. Automate everyday data science tasks using command-line tools
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Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics
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Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition
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Tableau 2019.x Cookbook. Over 115 recipes to build end-to-end analytical solutions using Tableau
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Natural Language Processing with PyTorch. Build Intelligent Language Applications Using Deep Learning
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Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
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R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5
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Hands-On Machine Learning for Cybersecurity. Safeguard your system by making your machines intelligent using the Python ecosystem
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Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow
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Apache Kafka Quick Start Guide. Leverage Apache Kafka 2.0 to simplify real-time data processing for distributed applications
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QlikView: Advanced Data Visualization. Discover deeper insights with Qlikview by building your own rich analytical applications from scratch
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Bayesian Analysis with Python. Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ - Second Edition
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Julia Programming Projects. Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web
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Machine Learning with Apache Spark Quick Start Guide. Uncover patterns, derive actionable insights, and learn from big data using MLlib
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Principles of Data Science. Understand, analyze, and predict data using Machine Learning concepts and tools - Second Edition
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Deep Learning with PyTorch Quick Start Guide. Learn to train and deploy neural network models in Python
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Apache Spark 2: Data Processing and Real-Time Analytics. Master complex big data processing, stream analytics, and machine learning with Apache Spark
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Microsoft Power BI Complete Reference. Bring your data to life with the powerful features of Microsoft Power BI
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Numerical Computing with Python. Harness the power of Python to analyze and find hidden patterns in the data
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Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python
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Blockchain By Example. A developer's guide to creating decentralized applications using Bitcoin, Ethereum, and Hyperledger
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Hands-On Data Science with R. Techniques to perform data manipulation and mining to build smart analytical models using R
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Hands-On Image Processing with Python. Expert techniques for advanced image analysis and effective interpretation of image data
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Practical Site Reliability Engineering. Automate the process of designing, developing, and delivering highly reliable apps and services with SRE
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Recurrent Neural Networks with Python Quick Start Guide. Sequential learning and language modeling with TensorFlow
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TensorFlow Machine Learning Projects. Build 13 real-world projects with advanced numerical computations using the Python ecosystem
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Hands-On Data Science with SQL Server 2017. Perform end-to-end data analysis to gain efficient data insight
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Data Science Algorithms in a Week. Top 7 algorithms for scientific computing, data analysis, and machine learning - Second Edition
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Hands-On Artificial Intelligence for Beginners. An introduction to AI concepts, algorithms, and their implementation
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Hands-On Machine Learning with Azure. Build powerful models with cognitive machine learning and artificial intelligence
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Keras Deep Learning Cookbook. Over 30 recipes for implementing deep neural networks in Python
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Python Fundamentals. A practical guide for learning Python, complete with real-world projects for you to explore
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Learning Kibana 7. Build powerful Elastic dashboards with Kibana's data visualization capabilities - Second Edition
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Generative Deep Learning. Teaching Machines to Paint, Write, Compose, and Play