Jayani Withanawasam - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Sztuczna Inteligencja i Uczenie Maszynowe: Kompletny Przewodnik do Budowy Własnych Rozwiązań AI
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Before Machine Learning Volume 1 - Linear Algebra for A.I. The Fundamental Mathematics for Data Science and Artificial Intelligence
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Dylemat sztucznej inteligencji. 7 zasad odpowiedzialnego tworzenia technologii
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Data Labeling in Machine Learning with Python. Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models
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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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Analityk danych. Przewodnik po data science, statystyce i uczeniu maszynowym
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Przetwarzanie języka naturalnego w praktyce. Przewodnik po budowie rzeczywistych systemów NLP
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Podręcznik architekta rozwiązań. Poznaj reguły oraz strategie projektu architektury i rozpocznij niezwykłą karierę. Wydanie II
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Zaufanie do systemów sztucznej inteligencji
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Potoki danych. Leksykon kieszonkowy. Przenoszenie i przetwarzanie danych na potrzeby ich analizy
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Machine Learning for High-Risk Applications
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Computer Vision on AWS. Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker
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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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Practicing Trustworthy Machine Learning
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Transforming Healthcare with DevOps. A practical DevOps4Care guide to embracing the complexity of digital transformation
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Applied Machine Learning and AI for Engineers
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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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Inżynieria danych na platformie AWS. Jak tworzyć kompletne potoki uczenia maszynowego
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Głębokie uczenie. Wprowadzenie
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Simplifying Android Development with Coroutines and Flows. Learn how to use Kotlin coroutines and the flow API to handle data streams asynchronously in your Android app
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Tidy Modeling with R
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Fundamentals of Deep Learning. 2nd 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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Natural Language Processing with Flair. A practical guide to understanding and solving NLP problems with Flair
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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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Machine Learning with PyTorch and Scikit-Learn. Develop machine learning and deep learning models with Python
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Agile Machine Learning with DataRobot. Automate each step of the machine learning life cycle, from understanding problems to delivering value
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Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition
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Uczenie głębokie i sztuczna inteligencja. Interaktywny przewodnik ilustrowany
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Machine Learning with Amazon SageMaker Cookbook. 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments
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Practical Weak Supervision
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Deep learning dla programistów. Budowanie aplikacji AI za pomocą fastai i PyTorch
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PyTorch Pocket Reference
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Engineering MLOps. Rapidly build, test, and manage production-ready machine learning life cycles at scale
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Python. Machine learning i deep learning. Biblioteki scikit-learn i TensorFlow 2. Wydanie III
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Kubeflow Operations 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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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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Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks
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Mastering Azure Machine Learning. Perform large-scale end-to-end advanced machine learning in the cloud with Microsoft Azure Machine Learning
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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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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 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 TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition
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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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Java Deep Learning Cookbook. Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j
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Google BigQuery: The Definitive Guide. Data Warehousing, Analytics, and Machine Learning at Scale
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Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications
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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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Deep learning Głęboka rewolucja. Kiedy sztuczna inteligencja spotyka się z ludzką
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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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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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Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
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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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Hands-On Machine Learning with IBM Watson. Leverage IBM Watson to implement machine learning techniques and algorithms using Python
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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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Deep Learning. Praca z językiem R i biblioteką Keras
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Neural Network Projects with Python. The ultimate guide to using Python to explore the true power of neural networks through six projects
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Ensemble Machine Learning Cookbook. Over 35 practical recipes to explore ensemble machine learning techniques using Python
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Generative Adversarial Networks Cookbook. Over 100 recipes to build generative models using Python, TensorFlow, and Keras
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Hands-On Machine Learning for Algorithmic Trading. Design and implement investment strategies based on smart algorithms that learn from data using Python
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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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Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python
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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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Practical Site Reliability Engineering. Automate the process of designing, developing, and delivering highly reliable apps and services with SRE
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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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Machine Learning in Java. Helpful techniques to design, build, and deploy powerful machine learning applications in Java - Second Edition
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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 Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
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Machine Learning with scikit-learn Quick Start Guide. Classification, regression, and clustering techniques in Python
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IBM Watson Projects. Eight exciting projects that put artificial intelligence into practice for optimal business performance
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Python Reinforcement Learning Projects. Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
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CompTIA Project+ Certification Guide. Learn project management best practices and successfully pass the CompTIA Project+ PK0-004 exam
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Mastering Arduino. A project-based approach to electronics, circuits, and programming
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Hands-On Artificial Intelligence with Java for Beginners. Build intelligent apps using machine learning and deep learning with Deeplearning4j
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Hands-On Transfer Learning with Python. Implement advanced deep learning and neural network models using TensorFlow and Keras
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Hands-On Convolutional Neural Networks with TensorFlow. Solve computer vision problems with modeling in TensorFlow and Python
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R Deep Learning Essentials. A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet - Second Edition
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Python Artificial Intelligence Projects for Beginners. Get up and running with Artificial Intelligence using 8 smart and exciting AI applications
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Hands-On Ensemble Learning with R. A beginner's guide to combining the power of machine learning algorithms using ensemble techniques
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Deep Learning. Praktyczne wprowadzenie
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Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications
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Hands-On Computer Vision with Julia. Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence
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Machine Learning with Core ML. An iOS developer's guide to implementing machine learning in mobile apps
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Hands-On Data Science with Anaconda. Utilize the right mix of tools to create high-performance data science applications
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Machine Learning Solutions. Expert techniques to tackle complex machine learning problems using Python
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Hands-On Automated Machine Learning. A beginner's guide to building automated machine learning systems using AutoML and Python
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Splunk 7 Essentials. Demystify machine data by leveraging datasets, building reports, and sharing powerful insights - Third Edition
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TensorFlow Deep Learning Projects. 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
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Practical Convolutional Neural Networks. Implement advanced deep learning models using Python
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Deep Learning Essentials. Your hands-on guide to the fundamentals of deep learning and neural network modeling
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Deep Learning for Computer Vision. Expert techniques to train advanced neural networks using TensorFlow and Keras
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OpenCV 3.x with Python By Example. Make the most of OpenCV and Python to build applications for object recognition and augmented reality - Second Edition
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Statistics for Data Science. Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks
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Neural Network Programming with Tensorflow. Unleash the power of TensorFlow to train efficient neural networks
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Zaawansowane uczenie maszynowe z językiem Python
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Neural Networks with R. Build smart systems by implementing popular deep learning models in R
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Apache Spark 2.x Machine Learning Cookbook. Over 100 recipes to simplify machine learning model implementations with Spark
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Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow - Second Edition
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Deep Learning. A Practitioner's Approach
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Mastering OpenCV 3. Get hands-on with practical Computer Vision using OpenCV 3 - Second Edition
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Deep Learning with Keras. Implementing deep learning models and neural networks with the power of Python
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Python: Deeper Insights into Machine Learning. Deeper Insights into Machine Learning
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Large Scale Machine Learning with Python. Click here to enter text
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Test-Driven Machine Learning. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones
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Apache Mahout Essentials. Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
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Applied Deep Learning on Graphs. Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures
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Technologie informatyczne a prawo. Prolegomena
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Deep learning Głęboka rewolucja. Kiedy sztuczna inteligencja spotyka się z ludzką