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Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2

Introduction to Giving Computers the Ability to Learn from Data; Training Simple Machine Learning Algorithms for Classification; A Tour of Machine Learning Classifiers Using scikit-learn; Building Good Training Datasets-Data Preprocessing; Compressing Data via Dimensionality Reduction; Learning Best Practices for Model Evaluation and Hyperparameter Tuning; Combining Different Models for Ensemble Learning; Applying Machine Learning to Sentiment Analysis; Embedding a Machine Learning Model into a Web Application; Predicting Continuous Target Variables with Regression Analysis; Working with Unlabeled Data-Clustering Analysis; Implementing a Multilayer Artificial Neural Network; Parallelizing Neural Network Training with TensorFlow; Going Deeper; Classifying Images with Deep Convolutional Neural Networks; Modeling Sequential Data Using Recurrent Neural Networks; Reinforcement Learning for Decision Making in Complex Environments
Thông tin trích dẫn: Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2. Sebastian Raschka#Vahid Mirjalili. NXB Packt Publishing, 2019.
Vui lòng truy cập địa chỉ sau để download và biết thêm thông tin chi tiết: https://lic.haui.edu.vn/media/Book%20C%C3%B4ng%20ngh%E1%BB%87%20th%C3%B4ng%20tin/python.pdf
Bạn đọc có thể tìm thêm tài liệu tại Thư viện ĐH Công nghiệp Hà Nội tại địa chỉ: http://lib.haui.edu.vn/opac80/

Từ khóa: Machine Learning;Python Machine Learning;Deep Learning;Scikit-learn;TensorFlow 2, Công nghệ thông tin, Sebastian Raschka#Vahid Mirjalili

18 p tailieu_haui 21/06/2022 99 3

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