James Pustejovsky, Amber Stubbs - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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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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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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Quantum Machine Learning and Optimisation in Finance. On the Road to Quantum Advantage
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Głębokie uczenie. Wprowadzenie
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Machine Learning with PyTorch and Scikit-Learn. Develop machine learning and deep learning models with Python
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Practical Weak Supervision
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Python. Machine learning i deep learning. Biblioteki scikit-learn i TensorFlow 2. Wydanie III
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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 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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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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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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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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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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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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Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
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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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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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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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Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python
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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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Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
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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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Hands-On Transfer Learning with Python. Implement advanced deep learning and neural network models using TensorFlow and Keras
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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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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 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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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 for Computer Vision. Expert techniques to train advanced neural networks using TensorFlow and Keras
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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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Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow - Second Edition
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Mastering OpenCV 3. Get hands-on with practical Computer Vision using OpenCV 3 - Second Edition
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Large Scale Machine Learning with Python. Click here to enter text
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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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Natural Language Annotation for Machine Learning