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Python Machine Learning for Beginners: Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow for Machine Learning and ... Learning & Data Science for Beginners)
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Python Machine Learning for Beginners: Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow for Machine Learning and ... Learning & Data Science for Beginners)
Python Machine Learning for Beginners: Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow for Machine Learning and ... Learning & Data Science for Beginners)
物品 #: 39108996

Python Machine Learning for Beginners: Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow for Machine Learning and

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物品 #: 39108996

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產品詳情

Learn Python Machine Learning from scratch with NumPy, Pandas, Matplotlib, Seaborn. Get started with Scikit-learn & TensorFlow. Explore Data Science for Beginners. Shop at Ubuy 香港
Publisher AI Publishing LLC
Publication date October 23, 2020
Language English
Print length 304 pages
ISBN-10 1734790156
ISBN-13 978-1734790153
Item Weight 14.6 ounces (413.91 grams)
Dimensions 6 x 0.69 x 9 inches (15.2 x 1.8 x 22.9 cm)
Part of series Machine Learning & Data Science for Beginners

產品敘述

Python Machine Learning for Beginners: Learning from scratch NumPy, Pandas, Matplotlib, Seaborn, Scikitlearn, and TensorFlow for Machine Learning and ... Learning & Data Science for Beginners)

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Data Modeling & Design Editorial Review

Python Machine Learning for Beginners is a hands-on guide to learning machine learning from scratch using Python, with a focus on practical application rather than theory. The book covers essential Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, and Tensorflow, and teaches how to use them for data analysis, visualization, and machine learning. Reviewers found the book ideal for beginners and late beginners/early intermediates of Python and machine learning. Some critics pointed out a few mistakes in the book and complained that certain concepts were not explained well or not at all. However, they found the code easy to follow and appreciated the author's code-focused approach. The book offers a great deal of context and useful tools for solving different machine learning problems. The deep learning chapter is especially well explained, according to reviewers, and offers an excellent overview of various techniques such as ANN, CNN, RNN, and LSTM. The book's publication quality is also praised, although reviewers note that the black and white print edition may be less than optimal for some sections that require color graphs and data. However, the author provides a link to download the color version in PDF format for free. Reviewers found the writing style of the book easy to follow, with step-by-step instructions and working exercises. Some critics noted that the book lacks clear instructions on where to find some datasets used in the examples, but customer support was responsive and helpful in providing the necessary links. Overall, reviewers recommend the book for anyone looking to learn machine learning using Python from scratch.

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優點

  • Hands-on guide to learning machine learning from scratch using Python
  • Covers essential Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, and Tensorflow
  • Code-focused approach with working code examples
  • Offers a great deal of context and useful tools for solving different machine learning problems
  • Clear writing style with step-by-step instructions and working exercises
  • Deep learning chapter offers an excellent overview of various techniques such as ANN, CNN, RNN, and LSTM

缺點

  • A few mistakes in the book

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HKD 284

現在訂購，約可在下列時間收貨： 星期三, 十月 14

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