Marek Chmel, Vladimir Muzny - książki
Tytuły autora: dostępne w księgarni Ebookpoint
-
Uczenie maszynowe w Pythonie dla każdego
-
The Data Science Workshop. Learn how you can build machine learning models and create your own real-world data science projects - Second Edition
-
Power BI i Power Pivot dla Excela. Analiza danych
-
The Deep Learning Workshop. Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras
-
The Deep Learning with Keras Workshop. Learn how to define and train neural network models with just a few lines of code
-
The Data Visualization Workshop. A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
-
The Computer Vision Workshop. Develop the skills you need to use computer vision algorithms in your own artificial intelligence projects
-
Practical Data Analysis Using Jupyter Notebook. Learn how to speak the language of data by extracting useful and actionable insights using Python
-
Uczenie maszynowe w Pythonie. Leksykon kieszonkowy
-
Uczenie głębokie od zera. Podstawy implementacji w Pythonie
-
Practical Synthetic Data Generation. Balancing Privacy and the Broad Availability of Data
-
Kompletny przewodnik po DAX, wyd. 2 rozszerzone. Analiza biznesowa przy użyciu Microsoft Power BI, SQL Server Analysis Services i Excel
-
Quantum Computing and Blockchain in Business. Exploring the applications, challenges, and collision of quantum computing and blockchain
-
Hands-On Exploratory Data Analysis with Python. Perform EDA techniques to understand, summarize, and investigate your data
-
Hands-On Machine Learning with ML.NET. Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
-
Człowiek na rozdrożu. Sztuczna inteligencja 25 punktów widzenia
-
The Practitioner's Guide to Graph Data. Applying Graph Thinking and Graph Technologies to Solve Complex Problems
-
Automatyczna analiza składnikowa języka polskiego
-
The Applied SQL Data Analytics Workshop. Develop your practical skills and prepare to become a professional data analyst - Second Edition
-
The Supervised Learning Workshop. Predict outcomes from data by building your own powerful predictive models with machine learning in Python - Second Edition
-
Algorytmy dla bystrzaków
-
The Data Science Workshop. A New, Interactive Approach to Learning Data Science
-
Building Machine Learning Powered Applications. Going from Idea to Product
-
Tableau Desktop Certified Associate: Exam Guide. Develop your Tableau skills and prepare for Tableau certification with tips from industry experts
-
TensorFlow. 13 praktycznych projektów wykorzystujących uczenie maszynowe
-
Machine Learning for Cybersecurity Cookbook. Over 80 recipes on how to implement machine learning algorithms for building security systems using Python
-
Praktyczne uczenie maszynowe
-
Mastering pandas. A complete guide to pandas, from installation to advanced data analysis techniques - Second Edition
-
Google BigQuery: The Definitive Guide. Data Warehousing, Analytics, and Machine Learning at Scale
-
R Bioinformatics Cookbook. Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
-
Practical Data Science with SAP. Machine Learning Techniques for Enterprise Data
-
Machine Learning for OpenCV 4. Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn - Second Edition
-
Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications
-
SQL for Data Analytics. Perform fast and efficient data analysis with the power of SQL
-
Hands-On Ensemble Learning with Python. Build highly optimized ensemble machine learning models using scikit-learn and Keras
-
Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
-
Uczenie maszynowe w C#. Szybkie, sprytne i solidne aplikacje
-
Advanced Machine Learning with R. Tackle data analytics and machine learning challenges and build complex applications with R 3.5
-
Deep Learning with R for Beginners. Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet
-
Mastering Machine Learning on AWS. Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
-
Hands-On Machine Learning with Microsoft Excel 2019. Build complete data analysis flows, from data collection to visualization
-
PyTorch Deep Learning Hands-On. Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily
-
Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
-
Mastering MongoDB 4.x. Expert techniques to run high-volume and fault-tolerant database solutions using MongoDB 4.x - Second Edition
-
Mobile Artificial Intelligence Projects. Develop seven projects on your smartphone using artificial intelligence and deep learning techniques
-
Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
-
Hands-On Business Intelligence with Qlik Sense. Implement self-service data analytics with insights and guidance from Qlik Sense experts
-
Mastering Hadoop 3. Big data processing at scale to unlock unique business insights
-
Mastering Tableau 2019.1. An expert guide to implementing advanced business intelligence and analytics with Tableau 2019.1 - Second Edition
-
Wprowadzenie do systemów baz danych. Wydanie VII
-
Advanced MySQL 8. Discover the full potential of MySQL and ensure high performance of your database
-
Machine Learning Quick Reference. Quick and essential machine learning hacks for training smart data models
-
Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition
-
Tableau 2019.x Cookbook. Over 115 recipes to build end-to-end analytical solutions using Tableau
-
Natural Language Processing with PyTorch. Build Intelligent Language Applications Using Deep Learning
-
Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
-
R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5
-
Python w uczeniu maszynowym
-
Hands-On Machine Learning for Cybersecurity. Safeguard your system by making your machines intelligent using the Python ecosystem
-
Computer Vision Projects with OpenCV and Python 3. Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
-
Bayesian Analysis with Python. Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ - Second Edition
-
Principles of Data Science. Understand, analyze, and predict data using Machine Learning concepts and tools - Second Edition
-
Apache Spark 2: Data Processing and Real-Time Analytics. Master complex big data processing, stream analytics, and machine learning with Apache Spark
-
Microsoft Power BI Complete Reference. Bring your data to life with the powerful features of Microsoft Power BI
-
Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python
-
Hands-On Big Data Modeling. Effective database design techniques for data architects and business intelligence professionals
-
TensorFlow Machine Learning Projects. Build 13 real-world projects with advanced numerical computations using the Python ecosystem
-
Hands-On Data Science with SQL Server 2017. Perform end-to-end data analysis to gain efficient data insight
-
Hands-On Machine Learning with Azure. Build powerful models with cognitive machine learning and artificial intelligence
-
Keras Deep Learning Cookbook. Over 30 recipes for implementing deep neural networks in Python
-
Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
-
Python Fundamentals. A practical guide for learning Python, complete with real-world projects for you to explore
-
Deep Learning. Uczenie głębokie z językiem Python. Sztuczna inteligencja i sieci neuronowe
-
Hands-On Neural Network Programming with C#. Add powerful neural network capabilities to your C# enterprise applications
-
Python Reinforcement Learning Projects. Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
-
Mastering Arduino. A project-based approach to electronics, circuits, and programming
-
Python Data Science Essentials. A practitioner’s guide covering essential data science principles, tools, and techniques - Third Edition
-
D3.js Quick Start Guide. Create amazing, interactive visualizations in the browser with JavaScript
-
Ethereum Cookbook. Over 100 recipes covering Ethereum-based tokens, games, wallets, smart contracts, protocols, and Dapps
-
Pentaho Data Integration Quick Start Guide. Create ETL processes using Pentaho
-
R Deep Learning Essentials. A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet - Second Edition
-
Blockchain Quick Reference. A guide to exploring decentralized blockchain application development
-
Building Machine Learning Systems with Python. Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow - Third Edition
-
Healthcare Analytics Made Simple. Techniques in healthcare computing using machine learning and Python
-
Microsoft Power BI Quick Start Guide. Build dashboards and visualizations to make your data come to life
-
Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications
-
Getting Started with Kudu. Perform Fast Analytics on Fast Data
-
PySpark Cookbook. Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python
-
Mastering Numerical Computing with NumPy. Master scientific computing and perform complex operations with ease
-
Big Data Architect's Handbook. A guide to building proficiency in tools and systems used by leading big data experts
-
Deep Reinforcement Learning Hands-On. Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
-
Hands-On Blockchain with Hyperledger. Building decentralized applications with Hyperledger Fabric and Composer
-
Artificial Intelligence By Example. Develop machine intelligence from scratch using real artificial intelligence use cases
-
Artificial Intelligence for Big Data. Complete guide to automating Big Data solutions using Artificial Intelligence techniques
-
Hands-On Automated Machine Learning. A beginner's guide to building automated machine learning systems using AutoML and Python
-
Modern Big Data Processing with Hadoop. Expert techniques for architecting end-to-end big data solutions to get valuable insights
-
Splunk 7 Essentials. Demystify machine data by leveraging datasets, building reports, and sharing powerful insights - Third Edition
-
TensorFlow Deep Learning Projects. 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
-
Feature Engineering for Machine Learning. Principles and Techniques for Data Scientists
-
Mastering Qlik Sense. Expert techniques on self-service data analytics to create enterprise ready Business Intelligence solutions
-
Mapping with ArcGIS Pro. Design accurate and user-friendly maps to share the story of your data
-
Building Smart Drones with ESP8266 and Arduino. Build exciting drones by leveraging the capabilities of Arduino and ESP8266
-
Fixing Bad UX Designs. Master proven approaches, tools, and techniques to make your user experience great again
-
SQL Server 2017 Machine Learning Services with R. Data exploration, modeling, and advanced analytics
-
Deep Learning with PyTorch. A practical approach to building neural network models using PyTorch
-
Ethereum Smart Contract Development. Build blockchain-based decentralized applications using solidity
-
R Deep Learning Projects. Master the techniques to design and develop neural network models in R
-
Spark: The Definitive Guide. Big Data Processing Made Simple
-
Machine Learning and Security. Protecting Systems with Data and Algorithms
-
Deep Learning for Computer Vision. Expert techniques to train advanced neural networks using TensorFlow and Keras
-
Mastering TensorFlow 1.x. Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
-
Computer Vision with OpenCV 3 and Qt5. Build visually appealing, multithreaded, cross-platform computer vision applications
-
Cacti Beginner's Guide. Leverage Cacti to design a robust network operations center - Second Edition
-
Blender 3D Printing by Example. Learn to use Blender's modeling tools for 3D printing by creating 4 projects
-
Learning Elastic Stack 6.0. A beginner’s guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana
-
Learning Google BigQuery. A beginner's guide to mining massive datasets through interactive analysis
-
R Programming By Example. Practical, hands-on projects to help you get started with R
-
SciPy Recipes. A cookbook with over 110 proven recipes for performing mathematical and scientific computations
-
SQL Server 2017 Administrator's Guide. One stop solution for DBAs to monitor, manage, and maintain enterprise databases
-
Big Data Processing with Apache Spark. Efficiently tackle large datasets and big data analysis with Spark and Python