Alberto Fernández Villán - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Introduction to Algorithms. A Comprehensive Guide for Beginners: Unlocking Computational Thinking
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Data Analysis Foundations with Python. Master Data Analysis with Python: From Basics to Advanced Techniques
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Uczenie maszynowe w języku R. Tworzenie i doskonalenie modeli - od przygotowania danych po dostrajanie, ewaluację i pracę z big data. Wydanie IV
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Wnioskowanie i związki przyczynowe w Pythonie. Nowoczesne uczenie maszynowe z wykorzystaniem bibliotek DoWhy, EconML, PyTorch i nie tylko
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Databricks ML in Action. Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide. The ultimate guide to passing the MLS-C01 exam on your first attempt - Second Edition
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Effective Machine Learning Teams
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Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet
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Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications
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Machine Learning Interviews
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TinyML Cookbook. Combine machine learning with microcontrollers to solve real-world problems - Second Edition
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Training Data for Machine Learning
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Interpretable Machine Learning with Python. Build explainable, fair, and robust high-performance models with hands-on, real-world examples - Second Edition
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Machine Learning with Qlik Sense. Utilize different machine learning models in practical use cases by leveraging Qlik Sense
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Analityk danych. Przewodnik po data science, statystyce i uczeniu maszynowym
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Delta Lake: Up and Running
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Architecting Data and Machine Learning Platforms
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Machine Learning with LightGBM and Python. A practitioner's guide to developing production-ready machine learning systems
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Machine Learning for Emotion Analysis in Python. Build AI-powered tools for analyzing emotion using natural language processing and machine learning
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Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models
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Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition
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Przetwarzanie języka naturalnego w praktyce. Przewodnik po budowie rzeczywistych systemów NLP
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Probabilistic Machine Learning for Finance and Investing
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Podręcznik architekta rozwiązań. Poznaj reguły oraz strategie projektu architektury i rozpocznij niezwykłą karierę. Wydanie II
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Graph-Powered Analytics and Machine Learning with TigerGraph
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Machine Learning for High-Risk Applications
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Applied Geospatial Data Science with Python. Leverage geospatial data analysis and modeling to find unique solutions to environmental problems
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The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
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Democratizing Application Development with Betty Blocks. Build powerful applications that impact business immediately with no-code app development
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Quantum Machine Learning and Optimisation in Finance. On the Road to Quantum Advantage
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Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition
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Praktyczne uczenie maszynowe w języku R
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Hands-On Healthcare Data
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Inżynieria danych na platformie AWS. Jak tworzyć kompletne potoki uczenia maszynowego
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Natural Language Processing with TensorFlow. The definitive NLP book to implement the most sought-after machine learning models and tasks - Second Edition
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Głębokie uczenie przez wzmacnianie. Praca z chatbotami oraz robotyka, optymalizacja dyskretna i automatyzacja sieciowa w praktyce. Wydanie II
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Designing Autonomous AI
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Building Data Science Solutions with Anaconda. A comprehensive starter guide to building robust and complete models
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Natural Language Processing with Transformers, Revised Edition
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Democratizing Artificial Intelligence with UiPath. Expand automation in your organization to achieve operational efficiency and high performance
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Distributed Machine Learning with Python. Accelerating model training and serving with distributed systems
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The Kaggle Book. Data analysis and machine learning for competitive data science
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Automated Machine Learning on AWS. Fast-track the development of your production-ready machine learning applications the AWS way
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TinyML Cookbook. Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter
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Transformers for Natural Language Processing. Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 - Second Edition
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Reproducible Data Science with Pachyderm. Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0
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Machine Learning with PyTorch and Scikit-Learn. Develop machine learning and deep learning models with Python
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TinyML. Wykorzystanie TensorFlow Lite do uczenia maszynowego na Arduino i innych mikrokontrolerach
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Matematyka dyskretna dla praktyków. Algorytmy i uczenie maszynowe w Pythonie
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Intelligent Workloads at the Edge. Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass
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The TensorFlow Workshop. A hands-on guide to building deep learning models from scratch using real-world datasets
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Machine Learning for Financial Risk Management with Python
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Azure Data Scientist Associate Certification Guide. A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam
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IBM Cloud Pak for Data. An enterprise platform to operationalize data, analytics, and AI
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Uczenie głębokie i sztuczna inteligencja. Interaktywny przewodnik ilustrowany
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Machine Learning Engineering with Python. Manage the production life cycle of machine learning models using MLOps with practical examples
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Reliable Machine Learning
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Conversational AI with Rasa. Build, test, and deploy AI-powered, enterprise-grade virtual assistants and chatbots
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Deep Learning with fastai Cookbook. Leverage the easy-to-use fastai framework to unlock the power of deep learning
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Machine Learning Engineering with MLflow. Manage the end-to-end machine learning life cycle with MLflow
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Practical Machine Learning for Computer Vision
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Wzorce projektowe uczenia maszynowego. Rozwiązania typowych problemów dotyczących przygotowania danych, konstruowania modeli i MLOps
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Machine Learning with BigQuery ML. Create, execute, and improve machine learning models in BigQuery using standard SQL queries
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Machine learning, Python i data science. Wprowadzenie
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Engineering MLOps. Rapidly build, test, and manage production-ready machine learning life cycles at scale
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Algorytmy sztucznej inteligencji. Ilustrowany przewodnik
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Umiejętności analityczne w pracy z danymi i sztuczną inteligencją. Wykorzystywanie najnowszych technologii w rozwijaniu przedsiębiorstwa
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AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide. The definitive guide to passing the MLS-C01 exam on the very first attempt
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Przetwarzanie języka naturalnego w akcji
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Automated Machine Learning. Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms
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Python. Machine learning i deep learning. Biblioteki scikit-learn i TensorFlow 2. Wydanie III
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Machine Learning Using TensorFlow Cookbook. Create powerful machine learning algorithms with TensorFlow
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Uczenie maszynowe w aplikacjach. Projektowanie, budowa i wdrażanie
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Python dla DevOps. Naucz się bezlitośnie skutecznej automatyzacji
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Machine Learning Design Patterns
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Kubeflow for Machine Learning
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Praktyczne uczenie nienadzorowane przy użyciu języka Python
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Wprowadzenie do uczenia maszynowego według Esposito
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The Natural Language Processing Workshop. Confidently design and build your own NLP projects with this easy-to-understand practical guide
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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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Machine Learning for Algorithmic Trading. Predictive models to extract signals from market and alternative data for systematic trading strategies with Python - Second Edition
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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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Building Machine Learning Pipelines
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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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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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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 Machine Learning with ML.NET. Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
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Jak myślą inteligentne maszyny
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Człowiek na rozdrożu. Sztuczna inteligencja 25 punktów widzenia
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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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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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Building Machine Learning Powered Applications. Going from Idea to Product
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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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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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Advanced Deep Learning with Python. Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch
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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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Machine Learning for Cybersecurity Cookbook. Over 80 recipes on how to implement machine learning algorithms for building security systems using Python
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Google BigQuery: The Definitive Guide. Data Warehousing, Analytics, and Machine Learning at Scale
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Programming PyTorch for Deep Learning. Creating and Deploying Deep Learning Applications
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Practical Data Science with SAP. Machine Learning Techniques for Enterprise Data
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Deep Learning
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Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications
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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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Uczenie maszynowe z językiem JavaScript. Rozwiązywanie złożonych problemów
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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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Machine Learning for Finance. Principles and practice for financial insiders
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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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PyTorch Deep Learning Hands-On. Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily
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Machine Learning with R. Expert techniques for predictive modeling - Third Edition
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TensorFlow Reinforcement Learning Quick Start Guide. Get up and running with training and deploying intelligent, self-learning agents using Python
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Machine Learning with R Quick Start Guide. A beginner's guide to implementing machine learning techniques from scratch using R 3.5
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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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Applied Deep Learning on Graphs. Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures
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Google Machine Learning and Generative AI for Solutions Architects. Build efficient and scalable AI/ML solutions on Google Cloud